{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "keras_03_mnist_dense_lrdecay_dropout.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.5.3"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/tensorflow-without-a-phd/blob/master/tensorflow-mnist-tutorial/keras_03_mnist_dense_lrdecay_dropout.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Lvo0t7XVIkWZ"
      },
      "source": [
        "### Parameters"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "cCpkS9C_H7Tl",
        "colab": {}
      },
      "source": [
        "BATCH_SIZE = 128\n",
        "EPOCHS = 10\n",
        "\n",
        "training_images_file   = 'gs://mnist-public/train-images-idx3-ubyte'\n",
        "training_labels_file   = 'gs://mnist-public/train-labels-idx1-ubyte'\n",
        "validation_images_file = 'gs://mnist-public/t10k-images-idx3-ubyte'\n",
        "validation_labels_file = 'gs://mnist-public/t10k-labels-idx1-ubyte'"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "qpiJj8ym0v0-"
      },
      "source": [
        "### Imports"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "AoilhmYe1b5t",
        "outputId": "adb3b814-cdfb-47a5-fc97-c2a7b97cee2c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "import os, re, math, json, shutil, pprint\n",
        "import PIL.Image, PIL.ImageFont, PIL.ImageDraw\n",
        "import IPython.display as display\n",
        "import numpy as np\n",
        "import tensorflow as tf\n",
        "from matplotlib import pyplot as plt\n",
        "tf.enable_eager_execution()\n",
        "print(\"Tensorflow version \" + tf.__version__)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Tensorflow version 1.14.0-rc1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "cellView": "form",
        "colab_type": "code",
        "id": "qhdz68Xm3Z4Z",
        "colab": {}
      },
      "source": [
        "#@title visualization utilities [RUN ME]\n",
        "\"\"\"\n",
        "This cell contains helper functions used for visualization\n",
        "and downloads only. You can skip reading it. There is very\n",
        "little useful Keras/Tensorflow code here.\n",
        "\"\"\"\n",
        "\n",
        "# Matplotlib config\n",
        "plt.ioff()\n",
        "plt.rc('image', cmap='gray_r')\n",
        "plt.rc('grid', linewidth=1)\n",
        "plt.rc('xtick', top=False, bottom=False, labelsize='large')\n",
        "plt.rc('ytick', left=False, right=False, labelsize='large')\n",
        "plt.rc('axes', facecolor='F8F8F8', titlesize=\"large\", edgecolor='white')\n",
        "plt.rc('text', color='a8151a')\n",
        "plt.rc('figure', facecolor='F0F0F0', figsize=(16,9))\n",
        "# Matplotlib fonts\n",
        "MATPLOTLIB_FONT_DIR = os.path.join(os.path.dirname(plt.__file__), \"mpl-data/fonts/ttf\")\n",
        "\n",
        "# pull a batch from the datasets. This code is not very nice, it gets much better in eager mode (TODO)\n",
        "def dataset_to_numpy_util(training_dataset, validation_dataset, N):\n",
        "  \n",
        "  # get one batch from each: 10000 validation digits, N training digits\n",
        "  batch_train_ds = training_dataset.apply(tf.data.experimental.unbatch()).batch(N)\n",
        "  \n",
        "  # eager execution: loop through datasets normally\n",
        "  if tf.executing_eagerly():\n",
        "    for validation_digits, validation_labels in validation_dataset:\n",
        "      validation_digits = validation_digits.numpy()\n",
        "      validation_labels = validation_labels.numpy()\n",
        "      break\n",
        "    for training_digits, training_labels in batch_train_ds:\n",
        "      training_digits = training_digits.numpy()\n",
        "      training_labels = training_labels.numpy()\n",
        "      break\n",
        "    \n",
        "  else:\n",
        "    v_images, v_labels = validation_dataset.make_one_shot_iterator().get_next()\n",
        "    t_images, t_labels = batch_train_ds.make_one_shot_iterator().get_next()\n",
        "    # Run once, get one batch. Session.run returns numpy results\n",
        "    with tf.Session() as ses:\n",
        "      (validation_digits, validation_labels,\n",
        "       training_digits, training_labels) = ses.run([v_images, v_labels, t_images, t_labels])\n",
        "  \n",
        "  # these were one-hot encoded in the dataset\n",
        "  validation_labels = np.argmax(validation_labels, axis=1)\n",
        "  training_labels = np.argmax(training_labels, axis=1)\n",
        "  \n",
        "  return (training_digits, training_labels,\n",
        "          validation_digits, validation_labels)\n",
        "\n",
        "# create digits from local fonts for testing\n",
        "def create_digits_from_local_fonts(n):\n",
        "  font_labels = []\n",
        "  img = PIL.Image.new('LA', (28*n, 28), color = (0,255)) # format 'LA': black in channel 0, alpha in channel 1\n",
        "  font1 = PIL.ImageFont.truetype(os.path.join(MATPLOTLIB_FONT_DIR, 'DejaVuSansMono-Oblique.ttf'), 25)\n",
        "  font2 = PIL.ImageFont.truetype(os.path.join(MATPLOTLIB_FONT_DIR, 'STIXGeneral.ttf'), 25)\n",
        "  d = PIL.ImageDraw.Draw(img)\n",
        "  for i in range(n):\n",
        "    font_labels.append(i%10)\n",
        "    d.text((7+i*28,0 if i<10 else -4), str(i%10), fill=(255,255), font=font1 if i<10 else font2)\n",
        "  font_digits = np.array(img.getdata(), np.float32)[:,0] / 255.0 # black in channel 0, alpha in channel 1 (discarded)\n",
        "  font_digits = np.reshape(np.stack(np.split(np.reshape(font_digits, [28, 28*n]), n, axis=1), axis=0), [n, 28*28])\n",
        "  return font_digits, font_labels\n",
        "\n",
        "# utility to display a row of digits with their predictions\n",
        "def display_digits(digits, predictions, labels, title, n):\n",
        "  fig = plt.figure(figsize=(13,3))\n",
        "  digits = np.reshape(digits, [n, 28, 28])\n",
        "  digits = np.swapaxes(digits, 0, 1)\n",
        "  digits = np.reshape(digits, [28, 28*n])\n",
        "  plt.yticks([])\n",
        "  plt.xticks([28*x+14 for x in range(n)], predictions)\n",
        "  plt.grid(b=None)\n",
        "  for i,t in enumerate(plt.gca().xaxis.get_ticklabels()):\n",
        "    if predictions[i] != labels[i]: t.set_color('red') # bad predictions in red\n",
        "  plt.imshow(digits)\n",
        "  plt.grid(None)\n",
        "  plt.title(title)\n",
        "  display.display(fig)\n",
        "  \n",
        "# utility to display multiple rows of digits, sorted by unrecognized/recognized status\n",
        "def display_top_unrecognized(digits, predictions, labels, n, lines):\n",
        "  idx = np.argsort(predictions==labels) # sort order: unrecognized first\n",
        "  for i in range(lines):\n",
        "    display_digits(digits[idx][i*n:(i+1)*n], predictions[idx][i*n:(i+1)*n], labels[idx][i*n:(i+1)*n],\n",
        "                   \"{} sample validation digits out of {} with bad predictions in red and sorted first\".format(n*lines, len(digits)) if i==0 else \"\", n)\n",
        "\n",
        "def plot_learning_rate(lr_func, epochs):\n",
        "  xx = np.arange(epochs+1, dtype=np.float)\n",
        "  y = [lr_decay(x) for x in xx]\n",
        "  fig, ax = plt.subplots(figsize=(9, 6))\n",
        "  ax.set_xlabel('epochs')\n",
        "  ax.set_title('Learning rate\\ndecays from {:0.3g} to {:0.3g}'.format(y[0], y[-2]))\n",
        "  ax.minorticks_on()\n",
        "  ax.grid(True, which='major', axis='both', linestyle='-', linewidth=1)\n",
        "  ax.grid(True, which='minor', axis='both', linestyle=':', linewidth=0.5)\n",
        "  ax.step(xx,y, linewidth=3, where='post')\n",
        "  display.display(fig)\n",
        "\n",
        "class PlotTraining(tf.keras.callbacks.Callback):\n",
        "  def __init__(self, sample_rate=1, zoom=1):\n",
        "    self.sample_rate = sample_rate\n",
        "    self.step = 0\n",
        "    self.zoom = zoom\n",
        "    self.steps_per_epoch = 60000//BATCH_SIZE\n",
        "\n",
        "  def on_train_begin(self, logs={}):\n",
        "    self.batch_history = {}\n",
        "    self.batch_step = []\n",
        "    self.epoch_history = {}\n",
        "    self.epoch_step = []\n",
        "    self.fig, self.axes = plt.subplots(1, 2, figsize=(16, 7))\n",
        "    plt.ioff()\n",
        "\n",
        "  def on_batch_end(self, batch, logs={}):\n",
        "    if (batch % self.sample_rate) == 0:\n",
        "      self.batch_step.append(self.step)\n",
        "      for k,v in logs.items():\n",
        "        # do not log \"batch\" and \"size\" metrics that do not change\n",
        "        # do not log training accuracy \"acc\"\n",
        "        if k=='batch' or k=='size':# or k=='acc':\n",
        "          continue\n",
        "        self.batch_history.setdefault(k, []).append(v)\n",
        "    self.step += 1\n",
        "\n",
        "  def on_epoch_end(self, epoch, logs={}):\n",
        "    plt.close(self.fig)\n",
        "    self.axes[0].cla()\n",
        "    self.axes[1].cla()\n",
        "      \n",
        "    self.axes[0].set_ylim(0, 1.2/self.zoom)\n",
        "    self.axes[1].set_ylim(1-1/self.zoom/2, 1+0.1/self.zoom/2)\n",
        "    \n",
        "    self.epoch_step.append(self.step)\n",
        "    for k,v in logs.items():\n",
        "      # only log validation metrics\n",
        "      if not k.startswith('val_'):\n",
        "        continue\n",
        "      self.epoch_history.setdefault(k, []).append(v)\n",
        "\n",
        "    display.clear_output(wait=True)\n",
        "    \n",
        "    for k,v in self.batch_history.items():\n",
        "      self.axes[0 if k.endswith('loss') else 1].plot(np.array(self.batch_step) / self.steps_per_epoch, v, label=k)\n",
        "      \n",
        "    for k,v in self.epoch_history.items():\n",
        "      self.axes[0 if k.endswith('loss') else 1].plot(np.array(self.epoch_step) / self.steps_per_epoch, v, label=k, linewidth=3)\n",
        "      \n",
        "    self.axes[0].legend()\n",
        "    self.axes[1].legend()\n",
        "    self.axes[0].set_xlabel('epochs')\n",
        "    self.axes[1].set_xlabel('epochs')\n",
        "    self.axes[0].minorticks_on()\n",
        "    self.axes[0].grid(True, which='major', axis='both', linestyle='-', linewidth=1)\n",
        "    self.axes[0].grid(True, which='minor', axis='both', linestyle=':', linewidth=0.5)\n",
        "    self.axes[1].minorticks_on()\n",
        "    self.axes[1].grid(True, which='major', axis='both', linestyle='-', linewidth=1)\n",
        "    self.axes[1].grid(True, which='minor', axis='both', linestyle=':', linewidth=0.5)\n",
        "    display.display(self.fig)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Lz1Zknfk4qCx"
      },
      "source": [
        "### tf.data.Dataset: parse files and prepare training and validation datasets\n",
        "Please read the [best practices for building](https://www.tensorflow.org/guide/performance/datasets) input pipelines with tf.data.Dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "ZE8dgyPC1_6m",
        "colab": {}
      },
      "source": [
        "AUTO = tf.data.experimental.AUTOTUNE\n",
        "\n",
        "def read_label(tf_bytestring):\n",
        "    label = tf.decode_raw(tf_bytestring, tf.uint8)\n",
        "    label = tf.reshape(label, [])\n",
        "    label = tf.one_hot(label, 10)\n",
        "    return label\n",
        "  \n",
        "def read_image(tf_bytestring):\n",
        "    image = tf.decode_raw(tf_bytestring, tf.uint8)\n",
        "    image = tf.cast(image, tf.float32)/256.0\n",
        "    image = tf.reshape(image, [28*28])\n",
        "    return image\n",
        "  \n",
        "def load_dataset(image_file, label_file):\n",
        "    imagedataset = tf.data.FixedLengthRecordDataset(image_file, 28*28, header_bytes=16)\n",
        "    imagedataset = imagedataset.map(read_image, num_parallel_calls=16)\n",
        "    labelsdataset = tf.data.FixedLengthRecordDataset(label_file, 1, header_bytes=8)\n",
        "    labelsdataset = labelsdataset.map(read_label, num_parallel_calls=16)\n",
        "    dataset = tf.data.Dataset.zip((imagedataset, labelsdataset))\n",
        "    return dataset \n",
        "  \n",
        "def get_training_dataset(image_file, label_file, batch_size):\n",
        "    dataset = load_dataset(image_file, label_file)\n",
        "    dataset = dataset.cache()  # this small dataset can be entirely cached in RAM, for TPU this is important to get good performance from such a small dataset\n",
        "    dataset = dataset.shuffle(5000, reshuffle_each_iteration=True)\n",
        "    dataset = dataset.repeat() # Mandatory for Keras for now\n",
        "    dataset = dataset.batch(batch_size, drop_remainder=True) # drop_remainder is important on TPU, batch size must be fixed\n",
        "    dataset = dataset.prefetch(AUTO)  # fetch next batches while training on the current one (-1: autotune prefetch buffer size)\n",
        "    return dataset\n",
        "  \n",
        "def get_validation_dataset(image_file, label_file):\n",
        "    dataset = load_dataset(image_file, label_file)\n",
        "    dataset = dataset.cache() # this small dataset can be entirely cached in RAM, for TPU this is important to get good performance from such a small dataset\n",
        "    dataset = dataset.batch(10000, drop_remainder=True) # 10000 items in eval dataset, all in one batch\n",
        "    dataset = dataset.repeat() # Mandatory for Keras for now\n",
        "    return dataset\n",
        "\n",
        "# instantiate the datasets\n",
        "training_dataset = get_training_dataset(training_images_file, training_labels_file, BATCH_SIZE)\n",
        "validation_dataset = get_validation_dataset(validation_images_file, validation_labels_file)\n",
        "\n",
        "# For TPU, we will need a function that returns the dataset\n",
        "training_input_fn = lambda: get_training_dataset(training_images_file, training_labels_file, BATCH_SIZE)\n",
        "validation_input_fn = lambda: get_validation_dataset(validation_images_file, validation_labels_file)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "_fXo6GuvL3EB"
      },
      "source": [
        "### Let's have a look at the data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "yZ4tjPKvL2eh",
        "outputId": "88918e04-46ef-4cf7-81d5-0afb3177d6f2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 177
        }
      },
      "source": [
        "N = 24\n",
        "(training_digits, training_labels,\n",
        " validation_digits, validation_labels) = dataset_to_numpy_util(training_dataset, validation_dataset, N)\n",
        "display_digits(training_digits, training_labels, training_labels, \"training digits and their labels\", N)\n",
        "display_digits(validation_digits[:N], validation_labels[:N], validation_labels[:N], \"validation digits and their labels\", N)\n",
        "font_digits, font_labels = create_digits_from_local_fonts(N)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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8d9OnT9dab2lsbW1BRFi/fj1SUlLwyy+/wMTEBGfPnsXZs2f5dsbW1lYwnZMn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\ng8FgMBgMBoNRA/k/mM7P2K24nEgAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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/RKFeUFBATk5O4jX08PCgKVOm0JYtW2jLli3k4eEhru/iOE5SD7uQsvjgwYPN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\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "KIc0oqiD40HC"
      },
      "source": [
        "### Keras model\n",
        "If you are not sure what cross-entropy, dropout, softmax or batch-normalization mean, head here for a crash-course: [Tensorflow and deep learning without a PhD](https://github.com/GoogleCloudPlatform/tensorflow-without-a-phd/#featured-code-sample)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "56y8UNFQIVwj",
        "outputId": "17cd3545-c15d-4cc3-86e9-dc4b49c9aa70",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        }
      },
      "source": [
        "model = tf.keras.Sequential(\n",
        "  [\n",
        "      tf.keras.layers.Input(shape=(28*28,)),\n",
        "      tf.keras.layers.Dense(200, activation='relu'),\n",
        "      tf.keras.layers.Dropout(0.25),\n",
        "      tf.keras.layers.Dense(100, activation='relu'),\n",
        "      tf.keras.layers.Dropout(0.25),\n",
        "      tf.keras.layers.Dense(60, activation='relu'),\n",
        "      tf.keras.layers.Dropout(0.25),\n",
        "      tf.keras.layers.Dense(10, activation='softmax')\n",
        "  ])\n",
        "\n",
        "model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.01),\n",
        "              loss='categorical_crossentropy',\n",
        "              metrics=['accuracy'])\n",
        "\n",
        "# print model layers\n",
        "model.summary()\n",
        "\n",
        "# utility callback that displays training curves\n",
        "plot_training = PlotTraining(sample_rate=10, zoom=10)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "dense (Dense)                (None, 200)               157000    \n",
            "_________________________________________________________________\n",
            "dropout (Dropout)            (None, 200)               0         \n",
            "_________________________________________________________________\n",
            "dense_1 (Dense)              (None, 100)               20100     \n",
            "_________________________________________________________________\n",
            "dropout_1 (Dropout)          (None, 100)               0         \n",
            "_________________________________________________________________\n",
            "dense_2 (Dense)              (None, 60)                6060      \n",
            "_________________________________________________________________\n",
            "dropout_2 (Dropout)          (None, 60)                0         \n",
            "_________________________________________________________________\n",
            "dense_3 (Dense)              (None, 10)                610       \n",
            "=================================================================\n",
            "Total params: 183,770\n",
            "Trainable params: 183,770\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E0A7CSbW67EY",
        "colab_type": "text"
      },
      "source": [
        "### Learning Rate schedule"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2qz_k44U6_-f",
        "colab_type": "code",
        "outputId": "391be5b0-1cce-4f5c-fb4f-b571ae914dbb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 422
        }
      },
      "source": [
        "# lr decay function\n",
        "def lr_decay(epoch):\n",
        "  return 0.01 * math.pow(0.6, epoch)\n",
        "\n",
        "# lr schedule callback\n",
        "lr_decay_callback = tf.keras.callbacks.LearningRateScheduler(lr_decay, verbose=True)\n",
        "\n",
        "# important to see what you are doing\n",
        "plot_learning_rate(lr_decay, EPOCHS)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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M/e63MePdN7T/Zm59FyWzZ8E7ciQ6W/b3+q/9nbX3A7DhnOf/iou3vIVT7/tlxu8ovvgi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\n",
            "text/plain": [
              "<Figure size 648x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "CuhDh8ao8VyB"
      },
      "source": [
        "### Train and validate the model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "TTwH_P-ZJ_xx",
        "outputId": "d39781bf-4724-4c53-854c-bb9ff5bf34a9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 467
        }
      },
      "source": [
        "steps_per_epoch = 60000//BATCH_SIZE  # 60,000 items in this dataset\n",
        "print(\"Steps per epoch: \", steps_per_epoch)\n",
        "\n",
        "history = model.fit(training_dataset, steps_per_epoch=steps_per_epoch, epochs=EPOCHS,\n",
        "                    validation_data=validation_dataset, validation_steps=1, callbacks=[plot_training, lr_decay_callback])"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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BgTBIyjM1bjpxIk6ehJwml9Z0llMS5S2QXIgVjgh7vNV0oRME7Zd5viJGM+Zm\nmDpcZl7i1psrzxpn0DT+0hd+qgxLktSmwbzi/qx5Ig6RXsEH5fsBAO/a8n1smD8fwDxrTVjCtxiy\ncNaBjZaF2P5y7q6wBqfP0tARwt1Z1z2tnG7ZYCm0luWUNweeFdNNMdGh8y2wDhdmfn8rLT5O//Hj\nAIAfnXWYa+NyK267EbHGTLA6sM4zp2lRYD0ssB5jNzmeCJYyOnZaHWqCvHtKGJdvymOQEki8jyox\nhQsJ7EYkMcGiruuxJFikScSizokmGms0GpBluaM5KYpiXo9skrsoSSNpm0wmE3lO7DpVKhWoqhp5\nTnSdms2mIyFcmDmx60TlFHVOdJ0IIYETYfLmxK4TTbQXdU50W1EUM3FflDnRdaIy6mROdJ0URUGx\nWIw8J3adVFWNPCd2nSRJwvDwcOQ50XUCgOHh4chzoucjfYditwkhpqU4zLau62g2m5bjgPGe7Let\n63r7Pbzlhkx54h332qZzott2noLMSdd1xzoFTbAoFNiIqFQqsfjXJ41OkJdG3xhYWge27l4HVnIx\nwVIlR21aXYh1TQNkmfPCTPAV9WN4HdmCI6SXIUHD2VuuxC/JlQD2Ylr5xwSGjYEN+n7NKj0sC+56\nrfOA09gbQjvx1jI8m+o6QFz8NMLogDxXZJ0zoq9lmVXiJtFUZ1r1CTF5sHwIYD5eEI7F2uJC7JEN\n28tq6jaefR9Fp3Vg47qnhIEOYYGdSkhigsXR0dFYEixWKhVHgrywc8rlchgdHTX7RZ0TC16SvDDb\n3d3dGB0dNXmJMicW2WzWIqeocu9k3exzAMBNAOe27ZYQLq5zKZPJQNd1U05R5kS3R0dHzcR9UebE\notNziWJ0dNRxrYSZE0W9XrfQCTsnO08DAwOB5+C1TemEnRMhxGIJ5pW/sceyBtlWVdX0cAzb3w6q\n0MeBKDwRQhzrFBTChTgimk13K8pUphMGbgqYwouBtbV1cyGmu+stc5MiEUtiHNaFmKKmp/Dp+hex\nTTcugrw2gR+nrkVWa5cTIoT4vtA7LLAhLUBuYXx+bqeBQIBV//xWHLhXF8BJzOQGntLu44lqbQvd\nVVHXeAmiPCjy6DjYC2KBDeJnHJxcQLQTg/nRdKYQs7oQh42/NftZLOf+CH6W8BHknhLETZnrxu6w\nvAu1VSAeJO2ZuieezX6Ikychp8mlNZ3llER5CyQXQoGNCLcaqVOdThD4KXas26/Zp/WXvqa6uxC3\nLLAt5Vdqxb1KhLpl8l/Ld2EGPlm/EA1iuC0fIG3BOTu/CehtJdpPcbAcjuC/2LaK2V2R+QiznwAY\n6Eojn1YsYwXhyUtH9IubNCwW7wAnAAAgAElEQVSKfE65SZw8+HKsuQ9vfnBT0HaHKmSyTvyULf4x\nVlZengCeLsTM9yDeuWan26lOyLunhFofj8Zuh4wPVEKZFYiOpD1TJ/PZHBRx8iTkNLm0prOckihv\ngeRCKLARYXdlmC50gsR9EttfO6gCy3N/ou+mvjGwTBInQIck8eMwWazW98dd+/6LuX1oeRXkB/7D\n5NUviVPQF2e3RD1uIKRtRdZt+4PCHgMb9BVfh7e1Swfw8s4JFCsNB3/m2C60w5Rp0XWdK6+wSpcO\nZ0wvb6y4wZ7znuqriwsxa4FtungQ2zNzO2lzPhjYxrbz0gmC3FMCWYJDMiL0V4FOkLRnalx04kSc\nPAk5TS6t6SynJMo7TsRRQidOOnHTmmxMXc73MKrV6rSkEwRUmXJTwOiLeIOtAxs4C3Grb9NqgaUv\nwTpPI2OwZuZJ+PPAGea28sh1kNbe0bKceUwK4etm2qdgxrna29msdlGS09iz4AZXtv0T5pz90yfw\n01WbXPu78csr0ePFlVNeu0dZqTMaYlzKLHvO+1sWeUmcNO5vFpLPOdq0fHhoXw8Pry/gnjU7Qrlz\nB0GUe4r944h7O9u2+VdorwKdIWnP1Ml8NgdFnDwJOU0urekspyTKO04kvdzQna9fEhvdyYBI4hQR\nNGvXdKMTBEEtsF4xCK4W2NZfmuiG2ttYF2RvJYng7r0/AbJrLU6QnwEAKHddgP1z38QazPTo6Ux6\n4za/sK/YoV2IOQf4CZD8wVMI7DGwE7WmmZ3XmdTJPQbWL6uzlU6w/f7W1XYnN2UvapkaL/hZYO0f\nKLySOLmJzc8ib+nH/D7nlqcAACmZuLePgCD3lLitvgICnSJpz9TJfDYHRZw8CTlNLq3pLKckylsg\nuRAKbEQkzRUgLjrBshB7t1WCxMC6sEtpUisaTdpElYJAZVaIjAsa5+He7BXYq7EFpFHGZc2v42Fc\niWH0uvdjaAcxkjosii6KlZFAilrMolli2aZhLJe8pFf2BpqmMxYwZ383Ro0kTsFcgHl0dA5zcShA\nE9X2gysufYqybni0M94ANtB9dhusGiAG1seDmGvdDGPlDAvePSWMRdvtemjtdW3blqGAQHgk7Zma\nRBe9JLogCjlNLp04kcS5JU1OmW/shbhy+tvp1C7dyW235htXI7fPPtj/o2cDANZedz0kWcGuVavQ\nGCtCbzRw4IVfwLyTh3zHVEslPPrxT5r9Fn/pIuxz0rsAAJv+53a8+IMfQlZk9C4+CEd+5zpUd+3C\nM5d+BaVNhnffoVd9DYNHHhF90hwIBTYigtYpmip0osRj+rkQszGw9qayTxInaoGllitLHViPd2hC\njBffIrrxwzlfx2XbLwCpjWNvbSduSF+PM+v/CtXltA/jlsvd78aTrY+fpLlJnEyZUx7CuBBzj5j/\narruSo+1ftvhFssZho7TAhuMllfb8Wr8X17bLtz8bNasCywB8bTAulmu3bwSeP14SZzizuwb5Z4S\n2DPA0w1bmHEFoiMpz9S46cSJOHkScppcWtNZTkmU91TG3GWnYPXlXzMV2K3/dzfe/N8/xf7n/BNS\nPT2oDQ9j5fL3Y+67T/LVAaRMBkffdKPZ74Hlp2L2ie/E+Esv48Xvfg+H3fJfmLVwIeojowCA1f92\nJQaPeROO/vGN0JtNqKWSJ/0oSNYniikEWqx4utGJA1Q5bTQajmP2Ash2UCtUo6XAaq0YTjMG1uf1\nlqW6I70v1OU3mk6wR0sv4KvKLa59O3W5dOWJYYodIqqFSQ9RRsc1Uy9j8dL09tx5WYjdLIN8S6I7\nZzw3aLvM/ZM4+WO8xlhg4zbBBuCBEF4MrL8LseST4Zjtx3UN99kOC949JRzN9jUbrGV8FnOBv18k\n7ZmapGczRZw8CTlNLq3pLKckynsqY8aSQ1ArFFDZvgNjz69Fqq8P2Vmz8PzV38J973o3Hv7QR1Dd\nvgO1Xa/5E9N1S7/K9u2o7XoNux5ZhbnvORnp/n4AQLrfqOO765FV2O8jZwIAiCwj1evu/RgVwgIb\nETzlbDrQCatUyRLBl961yLJPojGwajsG1k7XLLVjO0A3aR1YXdfNuEe/BDqUAGut1Ba9C80Tvgzl\n/q8DAD6i3Iu1+r64tfkOR9ewdWAdxzluwkY7a+Skqbz7WKF5Y5nFhDp0Iaa77JmZnS7EuuvHBo2u\nTSA+3BTp8GqXJaEXBxO7wQJLwSbkYhUzb3dZexZifiOZqXnMA8/aaolntg0eNimZHdx7io+VN7Bn\ngNcxocUKdICkPVPjohMn4uRJyGlyaU1nOSVR3nGhdulOqKoKRelc7QpDZ+57TsbWu+9BbecuzF32\nHmz+7e9QLwzjhLvvgJRK4ffHHI9mAGXf0e/NwfrtTkwJBVZVVdRqNTQaDfOrSldXl7kfMNwFdF1H\npVIB0E6hbd8uFAoADPdWRVFQapm1M5kMUqkUJiYmAADpdBrpdBqlUgm6riOVSiGTyaBcLkPTNJTL\nZXR3d6NSqaDZbEKWZeRyOVSrVaiqCkmSkM/nTb4JIejq6kK9Xke9lZ23u7sb1WrV5CnsnOjvcrmM\n8fFxx5wA4ytUkDlVWhnb1FbipUKh4FpHq1gsmnN66l/egnq9bs4BACYmJlCr1VCpls194+PjKBTa\niZ0qZeMYAYzxW3OisqnUjZtPrV5Hs9mEpmsgTeNc8Lox1et1NFu+rfVaDWNjY8ge/kk89fBKvK3x\nIADgCuWneFmbi8f1gyx92eywtWoVE9U67NA1HQ2VP/7wyCjyegVSyhahoOvQdB2FQgHVahW6rqNa\nrVqyNAPAxPg4CgWFm/xKazYxMjICVW0AuoQa03d0dNRVHmNjY9wvkXSM8QnjXGmoKiYmJjBeHDfb\nlMtlNFQVjTpBuVx20FCbmrleZp9KBYVCwXE9NVTVoZnU6w2USla6tXrDPPd4afA1TYfa+jCi6xrG\nx8cdPLxWtJ7/9NzM5/PteReLKJcNFyP79cWD2qhjYmICuqZBbTZRKBRQKrXPg3KljGKxCE3ToKoG\nXyxGGblWXLIjGq7mumVO3d3d5vGRsSKqVeMeQXnWdDbjso1nVUW5XAYh7fULc98bHx933PfsstZ1\nQ8b0vqcxn6pGx4oYHtZRqzs10krFet+j66JrGuoNY4xmS872+14nc2Lve9PBxexHP/oRbr31Vjz/\n/PM49dRTccMNN7i2/f73v4/vfOc7qFQqWL58Oa677jozzOOVV17BeeedhyeeeALz5s3DNddcgxNO\nOGGSZhEvwoTDTCU6cSJOnoScJpfWdJZTEuU91TF32Xvw9CX/itrwMI6/7VfY8n93IT1zEFIqhV2P\nrEJly5ZAdNTxcWu/V41+s459Mx77xKex1xmnAX19qI+MIt0/A7OOOxYbfv4LLDr3HNOFOG4r7JRQ\nYBVFQSaTQSaTsbzQAXBs219K7NuDg4OW7Ww2a9m21y512+7u7jZ5itKfYubMmY59YeaUy+WQy+VM\nfuxzCspjLmsEgSstpdUuJxa9tpOQx393dzcGBhoAtpl9BgcHIMk7W226ABjW2nw+b84pWxwGAKia\ncfORlRQkqYmUooAQAkVRIMvup20mnYHSegHOZjPo6+sDAPyg7wsY3LkZS6SNSJEmbkhfj+W1r2Or\nJTNx+4aXzWUBOe2gTyQCpTW+/fbY3z8DgwN5VBtWBVSSDLvp4OAgMpnXQAhBNptFOm2l393Tg8HB\nQe6HA0VR0N/fj1QqBYkQpFIp8xidIw89vb1Ip4uceRjRA+msoRzIsmysW0/740g+n4csy0hn0tyX\nfR3EMYdcNmc5d+i5oSgKJMkql1Qq5aCbSqU8zz1CAFmRW78l9PT0ONrU9bb80pmMhR6VbU9vrzl2\nEEUmnU6ju7sbsixDkmQMDg5iR70t13wuj97eXhAiIZ2SHddILt/VnmPaeV4BgCxJAAh3ToBxftBr\nO2sq2+6uzZIkm3OzK+dB7ntdXV3mfvo3nbYliyDWe0yDCYzu6+3FwEA/tlad5182m7WuS+t8JESC\nohjyURTF0sa+XlHmNN0we/ZsXHzxxbjvvvssHzbt+NOf/oTrr78ed9xxB/bZZx+ceeaZ+MY3voHL\nL78cAHDuuefiqKOOwm233YY//OEPOPvss/Hkk09i5kzvzO1JRFdXl3+jKUgnTsTJk5DT5NKaznJK\norzjxJ5IdtX7+gOhTkwgN3s2snvvhXnvey8e/dgncN87hzDjDUvR/brXBaLj6LfodSb9159/Hp76\n6LmQUyn0HXIIjvj2NVh6xVfw9CVfxqZf/QaQZRx21dcwcMQbI83XDVNCgU0i6vV6LC9ESaMT51cr\n1cMFkY6SVqwXIk1kQ7MQa3q7uqrhQuztX+jGfp1k8cn6hfhd5jLMIkXMJEX8KH0dPlD/KqqtnG4d\n14F16U5gdQ1la7oGoWvpwznmVc7GMyswDIsmu82rGRumjI4rJ1w3ZqcLcqAs0y68UkzUVKRkgkbT\nxX86Anjyt5Yj0i1tvZM48cfwy0KscZI4eaHTmdvvKdvHqhiteLtlBXYp96hNLBAcy5cvBwA8/fTT\n2OLxJf2Xv/wlPvKRj2Dx4sUAgH/+53/GJz7xCVx++eVYt24dnnnmGdx+++3I5XJ473vfixtvvBF3\n3HEHzjnnnEmZR5xI2jM1LjpxIk6ehJy8MVZp4NQf/gXfXPY6HPm62YngKW4k8RxIopziqksfls4/\n3LvC/J0ZGMDbfve/5jb1IAWAZS8+50rD3o/FgtNORd+J77QYU7KzZuGY//pRKD7DQiiwEWF3pZsu\ndOIEW4fL/kKfViSc//b9ceLivSz77XVgNaqD6LprDU5Hf1u8KB1/K2biM/Uv4Nb0vyNNmlgibcQ1\nqR/i/Mb5APjZZXlwa2YmorE1kAKW//GCVX66Rdn2VGDhLTPa13VOuvtHjVAlVcBRhPXwHw0CJXGq\nqsimZDSa8cXCsnHVXvOmipl3Eid+f0K8Y2Cty+y9bkDn55z9nvK26x4KNYbb9eDVT/dN0yYQBWvX\nrsXJJ59sbi9ZsgQ7d+7E8PAw1q5di4ULF1os/0uWLMHatWt96RaLRaxcuTIWHlesWOHfSEDIKSCS\nIqenCwSbR2Rc/X/P4uOvf3pPs2NBUmSUdESV07x58zA2NhYzN8lFlLlWq1WHfN/znvcE6isUWIE9\nhs+dsL9jH1UU6lSBbb21E8as5VdGh/u7pVL8VT8IX1U/im+kbgYALJMfxfPaQtzQXG6t0RoknVVQ\nY3UISyt7QJEIk/zHXkan3bzppUS4JFqic6VJnLS2WdPazoNPw8AZLImPrutcQs4UTgGSOLl1bmG8\npiKjSBjnH44E5lMId1hLUiVCHEp/kDqwso9XkF8SJzs6TeK0xzBF2U4ySqWSxa2d/h4fH3cco8e3\nbt3qS7e3txdDQ/41BP2wYsWKWOgARv4GrzCEqUoHiE9OcfIk5OQN6fmd+MlLz6K/vx9DQ0clgidg\nel9zcdLqRE7r1q2zWCX3RBKnsLTG1r6AJ75wkaWNnE7jbXf+1pPO2NiYZzibG3bt2hVZvkKBjQh7\nnOp0oRMn2Bg1s4arbdsOu7GPuhBLkuHiYNQ1dX/DJYzqyZJi6f6y+Q4cTF7BR5R7AQBfUn6NF/V5\neEg/0pMXCqoXOF2I+VYxhwuxmYTYWwNW5LYCaynFo1vH8LLAuh2i+82+fP3VsHy7ldHpsO5Qy7Bu\nH867j8dxiRjzGq+q6M+nzDFiAZM42kXXN/cROM+NYC7E3i7ybMZo07rpMcNO597pPYWXrdk85mjb\n/ut3jxAIj66uLktiMfq7p6fHcQwwLKtJfKYEQdKeqUmUY5w8CTkFg+KRuyMMprOcknhedgIa9kbf\n9fZEDGxYWn2LD8I//P6u2Oh7wavKRRCIOrARkbS04UlLGQ5YXYjtcDtn7XGAGrXyBXQhtg7C/QkA\nuEI9G49pB7XG1PGd1Pexv/5qGOrB2XBxO/W7bGWJtfu1f9kVPy8FFvBWcnxdiD34tJfg8afjpBTJ\nXdRFyVNaJsxyvYlsip9BOyrYjyK+buwcDVZltFY3y6jkcyO31IH10qLNNp7kfBHknuJURIX5NIlY\nvHgxnnuuHd+0evVq7LXXXhgYGMDixYuxceNGixL73HPPmfGyUw1Je6Ym8dmcxHIl011ObJWDTjCd\n5ZTE87ITZDIZjI6OMqX/4nk+xvmc3VPPbF3XMTo62lGcsrDARkStVovlC0/S6MQJlSk3E/Qri13J\n0VsWWF3XW7GkPrVH2TqwHiqiCgWfqX8Bd2QuwzzyGnpIBTco38J7m1eiCG85usU5tmP+rAxaE//4\n3ywo3wqrwLKlY21WaO8kTi4uxLa+brVVvWJgNS24+mnQce7zqyvqSdO2rUgENGoz20oOFte9mRcD\na03iBM/xgtaB1Tz8wS0uxLa/fu2joNN7iqert931nPkrlODgUFUVqqqi2Wyi2WyiWq1CURSHe9kZ\nZ5yBz372szjttNMwe/ZsfOtb38KHP/xhAMCiRYuwdOlSXH311bjsssvwxz/+EWvWrMHPf/7zPTGl\njpG0Z2oSn81x8iTk5A363ItLgZ2ucoqTTty0omL27NnYvn07hoeHoes6NE2LxXoaF504aVWrVeza\ntStwe0IIMpkMZs+OnthMKLACFuyu0lmmC7HPy6ndAtts+RQS4nRD9hrHsZ9zYBi9+GT9QvxP+grk\nSQ37ke34z9T38LHGP0eSg5tRzE7LVKx9xlCYmwqrjNsVP54l1GzryqtxRLVZYLlZiN1ciHmKscfi\n8MjYrZFBVBe3Nim5PUImFa9zSdsC671oOnSuCzErK/ckTt7yY12Pg8XAerIaCxwx0EH7RTwmYMU1\n11yDq6++2tz+zW9+g0suuQRnnXUWjjnmGDz66KOYP38+3vnOd+KCCy7AsmXLUK1WsWzZMlx66aVm\nv5tvvhmf/exnsXDhQsybNw+33HLLlCyhIyCQNIhQiL9fKIqCefPmmdsiVjheCAU2IpJW9yqJNa/s\ndRlZuCoCPBdiAHLLPTSI+ya/TA1/vOf1hbi48Sn8IP1dAMDb5Gdxif5LAG9wHcOMgQ34ZDJiG/n7\neaC7JdJWaohN52XJRSqjY+vr1k7Tdde1avpZwznjWfc5LbhhjG925YlV+LOtWrFxK0OuSiZjQiSc\nJE5sfVRXC6yvC3G42XQ69yj3FItV2t/LmWnLWJeFBhsYl156qUURZWEvq/O5z30On/vc57ht9913\nX9x11+TEPe1uJO2ZmsRncxLrbU53OSmc+u5RMJ3llMTzMk4IOcULEQMbEV7xnVORzu6wvGrMS7uZ\nPdenj12pM1xgdVMxgB78BdctiZMdd2vH4LvqP5rbn1LuwvxX/y/YIDx4xSWyPPnRIW2lxuKGHKKM\njkbl58IItd6a1Xa5LsQutMOY+FySQTnG8yXjrjQrIS2wP121Cet2Tvi2A6wfENqViV0sqfAro8Mf\nQyLeMcE8BdYziVOHmmBc96ZQZXSE9irQIZLyTI2bTpyIkychp2CIKyv8dJZTEs/LOCHkFC+EAhsR\ntVptWtKJE40GW0fSWgLHTSlyc73UW0mcAO+XdgLCzfLrpyx+W/0A/th8o7l9xLOXY7C4htvWzy3X\nwZO9vidjYeVRZt1VJYlY+pCWNTdoEidOmCkzktMCy2sbJomTF5zxzdGSALm1YGOGTQusB71vrHgJ\n7//hX3zHAxgZ+Lj50kP287sZ4IODX5w4L4mTJy8dvi9FuadEdSHWPY4JCIRB0p6pSXw2x8mTkJMP\naAxss9k5LUxjOcVIJ25acUHIKV4IBVbAgj0dr2G3wDZtiYKCuBCbvy37/WIXJXyx8Vm8pM0FAMha\nHW976ouYhRH3sVxpOdvxFA4/nggBZFN/tVpiLS7EQTQq++5WHz8XYt2jjI59bVi6AdnoSMuy90wx\nhVSzfhbYVueaGiyxBpsYzM0dGoBZ79YuMpVJzuSehdgnppXRYHXbX277SbBmBhkiTKZpnSG6u+Lx\nBQQEBCYLgWrKCwgIhIZQYCMin89PSzpxgo2BDfoy6sxUa7iMyrLUsn5xzHZsf/AVyyDDTyCPTzQu\nwphuyDJf24Ub09cjDVs6dmpFBne3c2xHEicDfmVTCGBaYLkZfFvwtcC6exAzSZxcXIgtHFvhV77H\nQofjiqzD6U7rR9Esq8SBJYmT4h0zHVW5s8TAusiVwPlxohkgC7Ek8ZVjCpZnLx7gfygQotxTgroA\nO5I/sdbl0KMKCLSRtGdqEp/NcfIk5BQMckwxsNNZTkk8L+OEkFO8EApsRCStnlMSY8d4PPlZY+wv\n/jSJk6GYEleXWG5/9mdABfoVfTY+17gAeuvSOEJ6GV9TfsIf1UWp5JXR4fHsdCF28mqPgW0f81eI\ngFYMLHd/66/DAutULNxk12g642vZrYmain+7Yy2qTQ+3a98dbUjERYlrweJC7FMHNrT7MycGloWf\nZZ0dz225/JM4MeOZfz0+XnR4S+jEnZvtHy4GNgBjAgIeSNozdao8m/c0rekvp7joTF85JfG8jBNC\nTvFCKLARUalUEk3nP95/CH7+sSNC0wlarzUI6vV2DKydavAYWB3QdeiaFsKK60x8FAYPam/A6oMv\nMrdPV+7HP8l/CNzf4ULMZCHWbfu9QAjfAhsqBtZ2yEym1TpgL6Pj6A9vOXqN/dNVm/DrJ7bgz1vd\nrchhyrDIhED1qD3LytOvDmzYTNKmC3crkZgb3MYL5kLMz1bN6xcsBrazB1OUe1Mcj8Ip/DwVSACS\n/mxOAuLkScjJG/QZo8YUAztd5RQnnbhpxQUhp3gxJcroqKqKWq2GRqNhBhx3dXWZ+wHDDK7rurkY\nuVwOABzbhUIBAJDJZKAoCkqlkrmdSqUwMWFkJU2n00in0yiVStB1HalUCplMBuVyGZqmoVQqobu7\nG5VKBc1mE7IsI5fLoVqtQlVVSJKEfD5v8k0IQVdXF+r1uqnY0f6Up7Bzor/L5TKKxaJlTm+Zl0Ym\nk0KtVgs0p1q1asqaysnN5aVYLLrOCQAmJiZQq9VM2dI+hUITTdW4iZcmSigUCo451WrWt9d6Q4Wq\nAU2tCU0FVJWg0bC59DKo1apotrIf12o1jI2NIZvNhs609tw+H0D2tdU4cOcKAMBXlJ/jZX0untUO\nRUM1xrfrPqOjoygoNTRIynqg9UZeKBRQrVYB6KhWq6jXrcHz4+MTKBQKZvZmXWtrqs1mEyMjI2g0\nGlBVDTVG3mPFcdd5FItFy9pIAJoA1NYYlZpxrKk2MTExgeJ4OytvuVxGs9lEvV5DuVzm0i9X65bt\nSqWKQqGATCZjylzXCVRVhW4LN1UbDZRtN896o2Gee/TcoFAkgoaqo9FotujqGB8fN+enMYXimw1D\ntvV6zby+8vm8mUiDyoygfU+wj2fhq25cR1qziaamoVAooFRuz71SqaBYLELTNKiNBsaLRaucmHlW\na1aZUWhNFbDNiS3EPj5RMu8v1db16qWkNjUN5XIZhBBz/cLc94rFonmPmGCuZRa6rqNWq5l8VRpt\nfsaKRQwPE9TrzmuvWqtZ7nt07XRdR711fatqk3uP6GRO7H1vKrtOCQgICAgI/D1jSiiwiqIgk8kg\nk8lYXugAOLbtLyX2bXvBXnut0kwmE2g7l8uZPEXpTzEwMODgMcyccrmc+T/dH2VO2exOAIasAaec\nWPT29nrS6+7uRnd3NwYG6gC2AQD6+noxODgDsrwdANDV3WUZg/I+qllflCVZhgQd6VQaIASSrEBW\n3E/bbDYLuaUY5rJZ9PX1AQBSqZRrHx5y+RyePPQKlH//Mg6T1kMhGr6f+i4+TL4BRVnA7dPb14fB\nwR6Mlq0KNrWiDg4OIpvdBUIIstksclmr3Hp6ujE4OAhZ/hsAI+5XaekDiqKgv78f6XQaNa0BhZlP\nzqOOV09PD5RUW8GVJIJms+0XLMuGLIkkmetGkc/nIUkSspms68s+ka1rkclmzXWl55KO9jqyUFIK\nslmbkqoorueeIhNABfQW7y/tLOHIbz2GP1xwLPbuzUBnPinMmtEDYBvS6YyFHv0o09WaJyEkUBHv\nbOveIysyCJEwODiIfGWsfTyXQ29vLwghSKdT6OuzXiOpdHut3c7fdDoFnTTQ09PDPZ7L5c1rO5Np\nXeNeJmRCzHWzK+f2e8RzOyr41C+exr2fPw6ZTKp1T2ivu6S4Xz/sfXCi2lZWe3t7MTAwgNTEqLOP\nbV2kVg1fQoh53qQUmXuPCDonv/ueQOdI4sdlOnanH5e11oeqqHOiH1noR+RO5qQoinl+sx/4ws6J\nrhP70SnKnNh1qrU+RkWdE10nylvUObHrROUUdU50nTRNC2wE4M1JlmWorQ9ymqZhZGQk8pzoNuU3\n6pzoOlEZRZmT/dyTZdnTsOE3J7pO9FyKOid2nWRZxvDwcOQ50XUCgOHh4chzss+B/WAe9UNsrVYz\njVZR5sSuE3ufizIndp0m++PylFBgBSYPuytfnj0Tn5v7rH23GQNLszPp7nVAAZpAx0kryrw0OYNP\n1i/EnZkvY28yin4yge/iP3CX+pNQdGiyJrOmrW2/F9jYSwqnC7F7f938x7a/tc/LhZgm0HKL1QWA\nhsfgQdzGvZL52CG3GFFtbssnfvcRvGvxLMscjnvdgDshZlyvubHwi4G1tAUniVOAGFi/84FbB9ZD\nYGFccTePVDBeVTFSrmNG3qmsutX8te9lt9sx4f7jt12ihf/wVEISPy6Xy+VYPi53dXV19HEZMF7w\nyuVyRx+X7WDlFGWO3d3dKJfLJi9R5sRixowZljZR5d7JutnnAID78ctt2+1jWBznUmqHocDSj9BR\n50S36fkUdU4sOj2XKNhz3Ku93z0CsM4j7Jyi8BRke2BgwPV4p/e9KB9i2bnFfZ/rZE6T/XFZxMBG\nRNJ82ZPox87WlzJjL336ODL7tl5oNU3rKB191NDenejHp+oXoqYb33oOwGacvP5rINA8yujYkjg5\nshDzY0J57alSw1NkKZK9lpQAACAASURBVJqauxJpV3oIo0yzx3nKhq63jnvIzq5MsgqIPW7XDl5C\naa/zoxXWaoknpXjkb8OWQeb3u7sDA+5KpB8s8cw2WQFt/h2x3Br72y0GFg4B6C6Kr277y6MVRhds\nnw/tfew9xb7O4cBRvL2ST3UwkoBA0p6pSXw2JzGGbrrKiT5zvZ7TYTBd5RQnnbhpxQUhp3ghFFiB\n3Qae3mMmz3Hpw60Dq7edQ3X4ZyE2M/b68OKNNp2n9UX418a55pEDR1bi88rtISgZsCsUvmV0CDEt\nhKzyrsNdsbHDriRSKrSPvYyOpS9oEid3PlUv8y9DBxYHX4Z+CG1FNl8EnJ0I2nO65aNvbI/hMgBV\n3IMnLWsnBvNi2cjaTBwfJ1gLrFsGZN75wDYNk8RJIiRU/VUqO7u8zvjx47j7uR2u55h9fLZ/GEWU\nZ7kVEBAQmDYQ9zUBgVghFNiI8Er4MpXpdJqE+HWz2vGYrFtAYDXBxYVYlqV2DU6PN1yL0soQ6zS7\n8v9qb8XN6rvN7S8ot+NNjcctbVxdJqnVE9ZnWKA6sHYLLHEqpV7WMbuyS+lQZahpK6PDKj3UhdiL\nTYcFlvktMfNmx7a2d2hArmMpsnG7anC+ZBsKGzB0yF44er8B3/WmbIc9L4mPBstI2joeIycvC6z9\nCKu0sv0sHyU4k5AkEsrKTGmzfXK5HJ7aPIYv3rY6VM1fO9ys79y2kUcREDCQtGdqXHTiRJw8CTl5\ng96eJTme1+3pKqc46cRNKy4IOcULocBGRFzlZpJGx447P3sMDpvXF6jtM5e9Hf/v00czPIUfzz4P\nU4kKqGoQwpdFHNK5Sv0wVmGpuX1e9Ua8RVptbrtZvNxiQf14YuditypbLHMhyui043GNbbsB1Wrx\nM+bkxWeD485LwfLq6kJs1189xlLkVgwsZ0xCDGXPfp64uShTpT54GZ32X7rOFmWfVV05NK0WWP4Y\nkuQso6Pp/N/tjyW6pf6tSYuEiyelTd1K/Ljtd9Cx0AzuJiysrgJxIWnP1N31bO4EcfIk5DS5mM48\nJfG8jBNCTvFCKLAR4VZWZKrTsePAvbsxqycdqG02JSOttE+papUpE2PGwHorDo7YQd3oZZbZgI8L\nMfu7w+uy35bMpgkZF+OLGMnMBQBkUcPNqWtwkvQ4r7uDD/sLvV8MrGGBpftYF2LdolB4xyfy1Wra\nvx0D624S87rBOZI4MWSsPAM8ld3pguo6lHmz4s2XxqYGXfPoFljvWq1uirHFAutCQOYwb3UV5yvM\nMleBDWmB5bgkT5Ta95SgMbDcDxXB2bDWBp7CD1aBPYekPVN317O5E8TJk5CTD1q3sWZMdWCnrZxi\npBM3rbgg5BQvhAIr4Iuor5HWLMBWKkFjYDXGjZWQtkXWc1zeGC4DumWhJQQ44cCZuP6DS3Hucfua\n+4voxm9efx226kb2vgxR8YPU9ThVesDVhdjiSqs797vOgzjtzoSl1YKXdYwpJWvOi+4H2oqJGQPJ\n9NV1vRUD644gig31+rZPV2/9Z2/rBmppdIuBBZzraReNGQOsUUUzoGXfFoPsACM/wvEXYK2ubhZz\nQpyfG6wWWNYE2/7DV2C5Q7iCjmONs2WOd5TEyQkvy7swxgoICEw3CC8TAYF4IRTYiIirpmBS6OwO\nN4KwtVcNPqzbWkuJkiQJBMT/5datPI9Lcy8lkhCCdx+yN1K22JWR7Hx8sHE5tkmzAQAy0XFt+kbM\nXPuzQGO7KVtuPBh/mZ02M7RnDKyLAketXGYMLKcDVTw9sxDb/GHZLZNnD2unVxIgO1KK++2KuhCb\nyZZ8ZBv2ZYLSY11z3dyi6ccWFkEs5jxF1BID69RfoetwcSEmIV2IrR8yACCdaXteuCWeYvsafFnP\nH/txXjvrfgGBzpCUZ2rcdOJEnDwJOXnDfN5L8bxuT1c5xUknblpxQcgpXggFNiIUJZ4SukmjEydk\nWTZ/t91ovfvY38XpC7UktTO7+rkQs+6e7fFdFNtASqRthw5sw0xcnv8Kntfa1tkFf/ka5Ieuha7b\n3GqZuVsVPDdlu72/nYW4/dfuRu0ZA2tTFewW3HYSJ46SoQeJgfWvA6uDr7CEL6PjocCCcGvWuilK\n7SzEHgNa6Lf+BnDNJXB6HARxIZY47sl+VlB3C2xUF+J2J0lu31M6scAG6WlRgoUWK9ABkvZMTeKz\nOU6ehJwCIiYjwXSWUxLPyzgh5BQvhAIbEaVSaVrSiRO1atX87bh1u97M+S7ENH7EEiPH621xW3aj\nyrb3f6jwWhAARakPZ9S/jCe0A8z9yoNXo/ehr8Gaj5Y4O8PfAksIm4XYqsnqASx6RjtYNALThdbF\nAmt35aRlYeygVj/vOrBtZdmNTpgYWAJ3ZVlqWWCDJsgyP4yE1GDthnDeb8B5ejctCix/CB4vrhZY\n6kKs61wF1nBHDo62C3F7H3tPCWrl172EAv9jhtu60GAFoiNpz9QkPpvj5EnIyRtmHdiYYmCnq5zi\npBM3rbgg5BQvhAIrYAFPgYjTvdjv1dRhgdV00wrojP50grD/ssps2BhY9rfDqtdGEd04q34pHmi2\nsxP3PH0TvqncBKmlcLkna/K2ChM4LbBAOzaVwisG1t7WHgNrKlamQuTsy5MRVZq8LLD2fhxDNudj\nhPtceIqaSdvM1mxt45qbilpgXSna6DPnlGd23ZYSbadriWUNUUbHbZ3ZVeW5EMtSVBdivqW4kxDY\nsImdzBxO0YcUEBAQSBSEZ4mAQLwIpMCOjIzgzDPPxJw5c7BkyRLcdttt3HYPPPAATjnlFCxYsABL\nly51HH/llVdwyimnYJ999sFRRx2F+++/vyPm9yT2tC/77z5zNH776TfFzk+cSKXbMXR2F2J3i6h1\nmyYhkiUpkAuxjRrnlxVBLHC8Ej5stwqyOLdxMYYXnGjuO0O5H99N/SdSUC1xpxYXTV8LLHHEwLZp\ntdt51eh0WAbpZ4AWAdUeA2vrq+t8F2LZzQJrGcvJqx9/XkgrsusxQ7HkZ23mjRfahdhsx4/Dts7R\nqcFay+jwZ004ZlM3hZJNGMY7h6k8goJngU2l2/eUMOeY334Bgd2JPf1s3l104kQSY+imq5xEDOzk\n04mbVlwQcooXga6oiy++GOl0Gi+99BJuuukmXHTRRVi7dq2jXVdXF8466yxceeWVXDrnnnsu3vCG\nN+Bvf/sbLrvsMpx99tl47bXXOpvBHkKUBEVx0jlodg8O3qc3dn7ihCK7KxxusL+MU0WL3vx13cfN\nlJDASklg2C2wnPHrSGH98d9Bc+kZ5r5T5MdwU+paZGGUE6Ld2tY8txjYNrgWWFitgJ7KhV1eLhZY\nMzGRpbO7629Kpoqw69Cm1td2IXYyF8aF2J5MyzIUWgpewLVvl9EJd7KwimEYy6LFhdg1iROHHmu5\nZa3jTBuuBZaQwLVbDdrW8wCwxsYErgMbcMgwNWIFBMJgTz+bdxedOBEnT0JOwRCXJ9t0llMSz8s4\nIeQUL3yjd0ulEu644w6sWrUK3d3dePOb34yhoSH8+te/xuWXX25pe8QRR+CII47gWlbXrVuHZ555\nBrfffjtyuRze+9734sYbb8Qdd9yBc845J675TBomJiZi+XKRFDq7w12vYomBjTYCtcA2m00QWfGN\nj3Nz/XV7eATKBByAT4OYAvU916NM8uh59r8AACfIz2CvsX/D6fii79i8jMGmQm+LhWWbenjxOhI+\nSaYCa+yl1kDTk9iehdiFrpsyyc7BLjeeHMOU0YE9ORZLmxhzcHwAceHBVMjChcCaSbQcrIEqgK0s\nxJxYboqmyyQlQjhldHwssDASnPFpBQevjM74xESbZ8+PJDp4ggyjpAaOnRVIFFRVRa1WQ6PRQK1m\nfKjr6uoy9wNAPp+HruuoVCoAgFwuBwCO7UKhAMCwCCiKYsZmZTIZpFIpTLTOx3Q6jXQ6jVKpBF3X\nkUqlkMlkUC6XoWkaSqUS9t57b1QqFTSbTciyjFwuh2q1ClVVIUkS8vm8yTchBF1dXajX66jX6wCA\n7u5u7Nq1y+QtypwIISiXyygWi5g1a1ZHc1IUBdls1pRT1DnRdSoWi9hnn30iz4ldp23btqG3tzfy\nnOg6TUxMYPbs2ZHnxK4TlVPUOdF1qlQqmDVrVuQ5ybIMVW0AAGq1GkZGRiLPiW7XajXMmDEj8pzo\nOlEZRZmT/dyr1WrI5/OR50TXaceOHejt7Y08J3adSqUS0ul05DnRdQKA4eHhyHNi5zA6Omq+p0eZ\nE53X2NgYBgcHI8+JXaedO3cin89HnhO7TuVyOfKc2HWi/PjBV4Fdt24dFEXBokWLzH1Lly7FQw89\nFGgAirVr12LhwoXo6ekx9y1ZsoRrybWjWCxi5cqVocZzw4oVK2KhM92wYaMEQMILL76AOXOsctqx\n3ThGEVSG64oAPcUeeeRhvNIFbN1q0Fr97LPIbHvG0afUaPcBgOL4BBoVICfraOpAUyd48aUCAL51\n9/m1z2OkRgBI2LhhA1asWM+dA0VTVcF7+X766aeBzcab9LpXiTme2mhg/d/+Bk1zquSPrFqFrT3A\nmPo2DKuj+IJyOwDgYHUNfpn+Ou6/u4rNr85ArUqwYsUKbNhk5emZZ56BvOVpDA/LAAgmJiZQkwCA\n4IUX1mLF2PPYuUNCsUbw5JNPmTw9t2aNqzxWr16NQoGY4xg3X4KJiRIAglrN2N61axdWrFiB53a2\n5/rHe+9FoyFj0yuvYMWKDWDXRa3XuHJ79dVXsWLFJgDAC9sMWjqAkdFRVGXdMt9nn12N7RVi2Tc8\nPGI7v5hzYXQEbk4jtWoVqgZsaY1v6FsK1r38MlZUXzLbvfaaIfPn174AQEajXncdjzevDa9IaDaN\n9VvPnN9/+5txrpXLMrZtLeHRVa9aaA0Pj5ryGh+fAFd2W7agUScWfsbq7TE2bKTr0L6ONE1DqbWW\nVnlUoOsk8LX64hZjrR77y+MYedE478tqe+yHHn7EVTa//8Mf0DLIo8jw+8STT6K2QceLo+1zimLt\n2rVYMfq8uV2pGOd8U9Pw8rp1ACSMj49z+Y/rHv6e97wnFjp/z1AUBZlMBplMBt3d3ZZj9m37S4l9\ne3Bw0LJNFTYK+wdar23KU9T+gPFyZucp7JzoCx7t18mcKFieoszRzkvUOVH09vZ2zBP7u5M5sWB5\nCjsn9mNBp+dSqvVhRlZk9Pf3R54T3aaKedQ5sYhr3QqFAnp7e33b+90j7OdS2DmxY9brdQwMDASe\ng9c2pRNlTuwcKpWK454SZk50W9d1U96d3ufy+bzjPIh6L6d/o8wpCgJZYFmlEzBOsgnm63wQlEol\nxwne29uLrVu3+vbt7e3F0NBQqPF4WLFiRSx0AGB8fNwhl6lM56kVLwHbNuGg1x8EjK+1yOnusWeB\n4Z3mdlAZrnx+C7DG+EBx3HHH4aDZPfjjxGo8WdiBQw89FENvmO3oM1Zp4F//2v5Yke/qQl9OQV4h\n0ImERlPHgQcMApvWc8c8+OCDsXW0Cmx9Bfvvvx+G3mVkCL6naJ0DRTqdQqWiOvYffvhhOOngvQEA\nG1ZuwN2bjfGUVAr77z8XD+7cDMDa75hj3ozD5vdhR7GKtz6Zwriex1dS/w0AWCJtxOLt1+PZva/C\nhqqMoaHjsfZP63Dvlo1m/0MPPRRDS2fjF9v+ivXjo+jt6UY2JWNzqYiDFy/G0DELcOfIM6iNVHDY\n4fsBL60GABx40GJg40vg4ZBDlmDD6u3A2AgAIJPOYKJRRy6fB6oVEFkBmk3MnDkTQ0NvxPgTW4D1\nxpq94x3vwNeffQgLF87B0NDrgVX3mnS78jmM1quO8ebOm4uhoUMAALse3YTbN74E6EBfXx96cylg\nrGC2XfqGpcjsKAFbXzH3zeifgaGho9oEmTH3mjUTGB7mzjOXy6Guapg/fxaGhhZD03R88dE/YdGi\nAzD09v3Ndv+z6ylgtIBFBxwIbFqPbCaDoaG3csdjsWD+fAwNLcaaP67DAztewdDQu/DXV0aANU8A\ngHmuXfPCw5g7tw/HHrMAWP0Xs393bx8wUTR4bcnejvlz5+LF8V0YGnqXuW9HsQo8YXwsnD9/AYaG\nDgIA/GF8NVDYARCCfFceqJYttLq68ijUKjjppJMCua5tWLkB2LQeRx55JI59nfEw27xzGHj8SQDA\nm445Bnjur9y+J554ommRf22ihq888SAA4I1vfCP+4fWz0Lu+AKx9ytLnoIMWY+jNC8ztbz7/IFCv\nQSISFi1aCLy6AT09PRgaOsbSL857uMD0RJrJvTCd6MSJOHkScvKGGQNL4omBna5yipNO3LTigpBT\nvPC9orq6ujA+Pm7ZVywWuV+8JoNOUpC0E7FTOrvDhTiKb73dBZSW0SE0BtbXhbgdA8vaSN1cmAOV\n0QkQA8vDzc2T8aXGJ9FsXWby8Dqct/F8zNe3evLEDmyW0bHxEjiJk+7mQmz89Uzi5BkD6/8wprxT\nV2ROCKxjZC/ZZlLu39tIy2XW5nHtCuo6HTgsiaHLjX21uWA7zxl3F+IffOhQfPTAJroyzvmxS8tL\n/mTfRdeXyj5o9mDqOsy2V5T29evlpu7FDxDOI5jGSwsIREVSnqlx04kTSXwBnu5yiis5x3SWUxLP\nyzgh5BQvfN9CFy1aBFVVsX592+L13HPPYfHixaEGWrx4MTZu3GhRYqPQSQqSVs8pibWcqmwMbMCb\ntz2GVWspYFqzaSgpuvcLsVvpnLBldNx4suyzKylMHCTFbc0TcH3fJajrhgvlQGMHftj4CsjONR5j\nM4o3L6uurTSOd4ZYW6IkUwFuKSyak2f7fHhs8hIHtTo5x6KbnC5hlBW96bSUU5h1YB3s8AfQNHee\nePCLgbW2JY6PE01dN2VmT+I0szuNwwf5HxLcaqxaQkY5QpSI+zEeaDM2BrZUblt1vUs1BaNt2efR\nRndpIyAQBEl7pibx2ZzEOpLTVU7tOrABvwL6YLrKKU46cdOKC0JO8SKQBXbZsmW46qqrUCqV8Oij\nj+Kee+7B6aef7miraRqq1SoajQZ0XUe1WjUDnhctWoSlS5fi6quvRrVaxZ133ok1a9Zg+fLl8c9q\nEhCmxuJUosND1A+HPJ782GTHUiRi1IHVwdSB9clCDJeyN67t3TIBs0qkd2Igc7/Lgcdyx+MTjYuh\nK0YcwCBGkfrFP2LuxBoXSpQHOC2wnLH8LLAs2pY544DdAmtXmGhdUzu8arK2+bdmIXbwBm9FJsyY\nBNaSMoHL6AT0PTDpESZjM0/pokmcbGQ1TTf5t1tSWeu6/ZrxS+LEjv21Ze2Pgaz1Owg0zpxYRdvr\nHGNhVay9GvIP6pzM1AICYZC0Z+rufDZHRZw8CTkFo+HnPRaWXpKQxHNAyGnyaU02AjnlX3vttahU\nKjjggANw7rnn4tprr8XixYvxyCOPYO7cuWa7hx9+GLNnz8Zpp52GV199FbNnz8b73vc+8/jNN9+M\np556CgsXLsQVV1yBW265BTNnzox/VpOApKXDjosO71SOmkGYLcNhWoQoTReSrOKRkiXDhRg6JKnt\nGuz1ILBYXV32swhigfUbxw4ndwQrtUNRPPWXqEhdxp7qGD6w9nwcJ632HEOya66gCiHrkuouD83m\npkss+9l2/Iesmw3WzQJrMcCS9k4dHOuorjtunl5r610HlnBL9biJJqwLcXsZ/LP78kg2dUCRrR8P\ngvRj5cMqlKycNB1Y9obZ+OCR7Xtx2wLrwyxDw86bzFy/gRXYANZWbr+gxAQEfJC0Z2oSy1QksQzH\ndJdTkJrzQTCd5ZTE8zJOCDnFC98kTgDQ39+PW2+91bH/2GOPxZYtW8zt448/HqOjo6509t13X9x1\n110R2EweklaQOInFiNPp9oUR9ObN6kWKRIwXax2QZRlNPdg7LeEofe5tw8fAmvtt226s0f7qnKPx\n4wXX4ZyNX0I/ikhrFfxX6hqc3zgff9COcrQnDH9s7Vi7G3UoF+IW7EqUW1wnTykE2sqYFxj91djm\nEAoaowkAaY8YWGMcp5LsxpPpQhxwbDa21uscdFPAm5oOmVq/7Z5kto8TLFj5WOrAWn47522WWwrs\nQqw7xkgxsTFeH0lcaXqorq5eDEw/ob4KREHSnqlJfDbHyZOQkzfaz794kjhNVznFSSduWnFByCle\nxHNF/R2iXC77N5qCdOJEtVozf4e1dAGGy6jeivdsNput+ENvF0P3xE18BqJYYN3GbyfysY/Rdufc\nkjsQn0l9DXrPHABAhqj4Qeo7eJ/0oIMeIcTkz8uyaI+ptDZ04cXRhecWa8ieJyNFClAHlu3noiAH\n2Wce07xjYHkJp9zIRbfA8mlXG03c+MAGqE0dIE4+NN3dhdgco9VnrNLAmq1Fsx9LgwfeRwY6VvAk\nTpRWu0O53M6U7HWOWZVkZ7sgoQQ+JAQEAiNpz9QkPpvj5EnIyRv03tbUmh3TAqavnOKkEzetuCDk\nFC+EAhsRmsOMMrXpxOTdYoGut3myK06uMakMI4pM2ooG2m/pXu+3hDgz9tp/s3CzDLu5Invto7Bb\nnoj1IF6R5qH+kTsxmp0PAFCIhm+nb8D+G35pac+LgW2RsIyhelpg+W69bhZY3bbPsO45Zxs6Bhb+\nLrL28R1jegxJCDGSOAVYc6CtkIV1j29ngbZy+ou/vIpv/2k9dk3UOSmcDAsstVrbLeZsa10Hzv7p\nE3j/D/8/e28eN0dxnos+1T37zLdrQxIIkJBAEovNYsCAsfEiGxOHxFy8n2CS/JJjx7k5cXy9xHZM\nHHziBDtx4mv7OM71cbzEgSTHxAQBjkGY1ezaVyQktGu+dfbp5f7RU93V1VU9Pf2VYPS5H37im66u\nfuutt2qm++13c0rw+C2wjAsxp9iysvbxGXFeoizEJvObEtWF2Ic4lzDeBYkHcYI46Jd7qmo6KqGS\np0RO4bADH2aHuSonlXRU01KFRE5qkSiwMcHGd84lOiLEVW5TuhezyOs78hhY73Na05wsxLbtut9E\neqglvj+Bz1H48PeJ6iwss6x1zrKJg4ZOx79d+C1ss7xamBdt+RL0R7/qmyRvgRWV0QnPECtzIe7O\nuQ25C7HOxCT7r/EosbzaNBOXYAw/vwJGOkiHxMBqBB1rcbTN2rMFlnPlDvUCIIIkTjaThbhLDOz2\nI5XOGDanqHp9WQqWyAJLwsfiIYqB1TRP3mEuxPxLj7DzYW0JEqhAv91TT+a9OS5U8pTIKSIUWQnm\nspz6cV+qRCIntUgU2JjI5XJzko5KsPWlvHjI8EdXVgFJ6Z4Lsa5rXgmTLspDb+3RYzm7XSdzIeZj\nQSka2fm4ufWneNZa4balHv4S3j/zHac3CSpODv3oZXT4U7LYSBHv1Bomk5AokZPIhThsxQOupCG9\ncxl5sgHSoRV41SAhJ3KJjRQvyswprH/QAgvoHbdrfmzZFjQtm1NUWQssmM/BGFitRxOsKAaW/f7G\nqQDBD81ul7DkXSJvgAQJoqLf7qn9eG9WyVMip3DQ3zpNEnbTK+aqnFTSUU1LFRI5qUWiwMZEvV7v\n3ukUpCNC3PeGzSYbAxtIM9N1LF0jzkO87bg50AQ6UdPR+92A48fARs1sG4UAe6lGgGmU8IHWp/GI\nucZtv6H6r7g99Q/QbStogaVZcCWWOR68uzHlJGiBtX1/3VaJ5RRwskSHgXDzFimXAQthmGzDYogI\nCZT8EbosU1J2kMcwObKJtYDuyqsoBjblxsCGj0FhWLbfhVjCoMUIl7JFn5WiW2A768/0rzN1nKPS\nEfbqNObScgu6v3uiuiaIj367p57Me3NcqOQpkVM46K+ZaaqJgZ2rclJJRzUtVUjkpBanru34VYaq\nH6N+o6MSrG99VNdOvwuxk4WYKmxRKLCKg7+Wq7i/NAZW8lnWB2Bi9yT93PhfVyl1PtSQw63tP8GD\ni7+HxUd/DgB4X+pBLK0a+F7pk35abgyrhCkenAtxtxhYvs3RjcQSEMXBsmRYy7MowZJo3LBphRWw\noS7EwSRO4muoS2yYVdA/dudvBMOmaJ6mZbtjRU2IZFjRXIid7Mv+MXuvAxscw2B+U6LWGhZ9pk25\ntIZayxTzJdx/tjv2bfdsxy1XLguZQYJXA4ZhoNlsot1uuy8si8Wi2w4AhUIBtm27D0r5fB4AAsfl\nchmAkxUzlUqhWq26x+l0GpWK41qfyWSQyWRQrVZh2zbS6TSy2SxqtRosy0K1WkU+n0e9XodpmtB1\nHfl8Ho1GA4ZhQNM0FAoFl29CCIrFIlqtllu3vlQqoVKpuPfVOHMihKBWq2F6ehqpVGpWc0qlUq6l\npFwux54TXafp6WnkcrnYc2LXaWJiAqZpxp4TXadKpTKrObHrROUUd050ner1OvL5fOw56bqOdqvt\nflcmJiZiz4keN5tNZDKZ2HOi60RlFGdO/DrRPRV3TnSd6F6KOyd2nRqNBsbHx2PPia4TAIyPj8ee\nEzuHWq3m/qbEmRNdp6mpKWiaFntO7DrNzMy4PMWZE7tOtVot9pzYdSoUCoiCRIGNCV2PZk041eio\nhC6Ige1myPEncdKch1jbqQNLrYmh8YcAk8mGaxeOF86PqFOv9iGvBq4tbAeAJjJ48uK/xq/t/xL0\nzXcCAK5p/QJDJ5p4BL/vY4FNdNMN3ZRp8MeckiSLgbUZi2JUJoIKf1C9DFMiwyy+BJ1YULZNwLhr\ngXaTOHkIt8AGY2Bl3UVSsWwbWierNB9Pyr5yYc8Ypu170cBexyu2/FRdZTmq5ZRaYH0xzEwMbJwk\nThxyKR1AOwIv/uMTlSb++emDOHfRAEZmzUUClUilUshms8hmsyiVSr5z/DH/UMIfj42N+Y551za+\n3IPsWNd1l6c417P8Dw8PB9rC5sAf5/N56LruXhd3TixYOcWZY6lUgq7rLi9x5sRiZGTEJ6e4cp/N\nuvFzAPxy6nVOVDaTk5Oz3kvpY45CradSGBkZiT0nejw5OYlCoRB7Tixmu5coJicnMTg42LV/t98I\nfi/1Oid2TNM0SQvtbQAAIABJREFUA9/fuHMcHR2Vnu/ld6/VagV46mVO9FjTNFfes/2dGxgYCHx/\n4/6W079x5hQHiQtxTPALNFfoRK0bGQXspuSViSiKY4qxwOq67tDoorx1cyGl+MgbzsIzn742mlVX\nMk7QJZaanPgYRzZ+1Wvnrb+2loLxzr/DfcVfc9surP8S/zvzl0ibVR8vtkSZ4RGIx5XFwLouxMFr\npTGwgrTAPgsc81fGYcASLOkHALlsRnqOdFyIAxZ1CUEviVNEzwB3nEjdA/2oBVbr1PGNco1hWVxW\nYGbNmX7hdWCj8SuywPoeBrpkuvY+B/vRvZZLa0ybnIZb0ofrG1UZT/CrjX67p6qioxIqeUrkFA76\nq6UqBnauykklHdW0VCGRk1okCmxMNJj4sLlER4S4yfNard7rwLLQNac0im0DtmV5SZzigBs/m9JQ\nyqYiuTYHY2DFXER1IZaw1GnU8L2h38fXjF93m16nbcd1v/xdoFZmeAiOKwKVX7Cd413kwgmq5Ilp\np7vckD2rnjOAKJa4F53ENAxpzLKbxCniCwxR5vgwBUkUAyvtLni5YdmAJsnczFvXKUzLb4E9Ot1k\nOvpp84p4VJd9j0ZnrdgYWCaGPY7yyCuzUWNg6eQ8xRW+4wQJwtBv99STeW+OC5U8JXIKhxcKoaZc\nyVyVk0o6qmmpQiIntTglXIj7Nc4mjr8570M/MzPjxmzMNs5G1/XYc6rXnU1M497YOJtWy+/2FzXW\nYXp6xr1manICeivt+tpXZmZQLqek6wQAsExYnYf4VqsFaDpM03TlJUKj3nDnUK/XMTU1hVwu58ah\nUDSbTZTLZdiSxED1Rt3dKyYznm3ZzhwED9PTU9Mol2284+vP+9qtzhjj4+NoNpuwbRuNRgO1WtXX\nb6ZSQblchmGa+Irxf6FYGsatje8CAMamt8L43jtRyP8ZTLOANsMTmyyLR7VWQ9vw5k554RUS07JQ\nqVRQqXo81WrOmtTr9UCxa8uyhHVZqVyz2SzabYdH23bo8/XGDMNAg+PdMEzf3mPRbreR0ghagixI\npmnCtm202y133QCg2fKOC4WCu/9q9Efbtr3+KbmFt9Fo+GLiyuPjqNfFcm81m5iamvTPy7TclzA8\nqhVH5k3uRnK8PI6m7cQqLRvJYl+5ilq9Dss00ex83wDHHbrZbPjmbXbWvFqrIa+ZXWNSaMKmWq2B\nZrOJarWKyckpl95MRV7svNlsol1vwzAMTM54e21mpoLx8TRabaft184bxtbDzm9Cs9V0+S0Wi764\nYLpvLNPZC7UW6fBQwTy88nE2CU4thN0fTmU6KqGSp0RO4XB/2RS9gZurclJJRzUtVUjkpBanhALb\nj3E2NIB6tv7nxWLRjYugiBOTomnarOJs8vkTALzaraycMlz5kqixDgNHvIfesdFRjBYz0LSXATh+\n92ExKgCQz2ZgwbEuZTJp2FoKWt2CFhLvmy/koVcdRalYKGBoaKjDk185yeVyGBsbk9bAyufzLn/p\ntDcPohFouu5YzThtZGBwEGNjo2hzChYdY3R0FJnsCRBSQy6XwwC3zgOlUoenlwAAPx24CdmBEbzv\n2N9AIzZSE3vw/8z8CT6W+hxS+tnudZmMPH4gny8glaq4x+lUCkBT4Frs7B92HTJZZx8VBfE2RNOQ\nTgUtsNlsxpVbKuUpQJqmuWVkKPRUCum0f100XQ98R13e0ymkdA0tQcKydDoFC0A2k3WvJ8RRXlh6\nNC6bjqtpxD1PEwyJkM/nUSqV3LUcGRlFvjol7JvL5TAy7P9O2wBSKR2aEwTrO1cqlVDuXMeeKQ0O\no11zFNWViwbx0sRxTDSBJcMlNwkHpU33M0W2UwInl8sjn892jUmheyjT+U3LZrMolT2FOhuSaj+T\nyaCYdfZHTfMyGpZKJYyOjiJ9/DgA4NJzTsPGK1fggi8+iEzavy6sBVnvyJjuhdq48/3LF4rA1Csf\nZ5Pg1IIqV81+o6MSKnlK5BQNqhxI5rKc+nFfqkQiJ7U4dTl/laHq7X2/0VEJ9oGS92iMFAOrk46b\nqY2UnorkQuxP4iNu75UPcQxsdBfNYBZipyVKBuTHht6Jj7U/Cos4D/XzjCP4u8ZnMDSz0+3TTSa+\nLMSdv8EsxEEqtI9sqilBUiVZFlppFmKe+5C31Jl0Rpj5GBC7EIvI0UNRDGwUN9mo5VVFMbA6IaGu\nvaJrKEvL5xUBAHtP1ALjW4IYWCqnqLmXRG66vhjYEDo97T9JdmR2H/Dr4PGW+BAn6I5+u6f2471Z\nJU+JnMJBf7Z0TU2izbkqJ5V0VNNShUROapEosDER5rZ5KtMRw3s8vnblvMhXtdqem2OvZT0AuFlu\nLZvWge2uPdBascF2cRKpSLGCXZSirpdLshBHGVojwE+tK/DIxX8DO+W8EBjDBN729O/gIrK7w4+c\nIcv2jyorw8MnzGH7yMropLtkIWZHFnFo284YrFLKJydi0TYMuQLrrmcoSy6oy6qvf9i+4v52rQPL\nj2c7e63bmrN026aXxOns+VSBrQquCUuSFm2z0nFZ5ZF3U45IyPvInYr6ysfLhebnSUEi5AS/Aui3\ne+rJvTfHg0qeEjmFg94HVcXAzlU5qaSjmpYqJHJSi0SBjYl2u3s5iFORTtgz4pd/Yw2+9f6LItMy\nDc8lM5AlNcLjLC2b4tTDdH78eykh4x9PfCxTKHw1ZAW8ipQUmVLj05GYLpo0IxFx/1DF5MiCq9G+\n+ceoa87bsqwxjR9k/gJXaFtC5cEnSpJJ3ZdwiWuTyahbHVjWAhvGn78Wq/gz4MTvykr30DXi1yrw\n0qDzl1oUo1pg+dq9YXNy3MsFe0aQ3MlHmzvL1oFdMJCFrhGcqDpKpf9Fg8ACS+QW2L+6fxd+uukI\nntk/iT+/Z7uvH9ufxqJSXni4S9HlCynOTBx+DQuPt0SDTdAd/XZPVUVHJVTylMipCxR7kMxZOSmk\no5qWKiRyUotEgY2JXlxITwU6itjgaHpEe82KCjBukJZTHoW6EIfdB6SKccCFWazwCC+NyLqMLb6k\nCW/Nk11PQJj6uTbsM67A3y/9CibgxCAXSRPfTX8Z5009GsITb/UVT0bEu8Xxy0NURkdIs+MGHqxw\nYwdK3/gUYI4eAZFaYN0+rNt4yMKJ6sCGKqWugux1jvLCgoWudXchZuOn2SzEGnHK0DTaVoBXket0\nWN3l/9x8FA/vOoH3fedpfP+XL6NlWMIsxOxMWkbQeiB2CffzxTY6L2RoE+/Czn72v0xxjxP9NUEE\n9Ms9VTUdlVDJUyKnaFD18zWX5dSP+1IlEjmpRaLAxkSxWJyTdFQilw/GwPbyEEqtbaZtI5VKOTS6\nEIhaRoWei+JyGmY1iwLW85nlPqwkDL2OKjxUmXw5vxIfzX4R1ewCAECWtPHBA3+Kd2mPCGk5Fmtv\nVBnfnrIRjEWU/cCJlDGRBdWCM+/AywKbutay19jCzwCQyWakFliKqOvixcB6bVEssBqzlqF8CNo0\n0tuLnLZpu+uuEYJ8WkedJpri1omnqrnu9wLrJ5zYWlqXdaZhCK2cbOKmpkCBjSoLChLpdVHQnT2x\nwCboBf12T+3He7NKnhI5hYP+avFJDONirspJJR3VtFQhkZNaJApsTLSY+LC5REeEuC9o2PIzfAxs\n1CROgGMts22vBInIJZGCSM7LhlNaB1bCFn1s/9uf7/FZy7q9+WI9UdmH931kKX762u9gn7UQAKDD\nwlfT38AH9AeCPLn/CwdnLHM+d7mum+SixPzasH2u1GEWWMuUuxB7PHEuxJI5CC2woZZ9+kGuGHpd\nZPVew2Ng+VOGZTFu3B0Ftu0osOzoYXVgZZZ1ywbynbqs0402E2/q9WsxrkUtM1r8ll8sQbd0cb/g\nfPz82r6/CRKEod/uqSfz3hwXKnlK5BQO90WcoiD+uSonlXRU01KFRE5qcUqU0elH9NtGfCU2Ya8/\nv6xvfdTkOizSnTeWpm07NUQ1rasLMQv2oT4jKPni9JFd24V25JQ0Hq27nj2E85d4JYi6Kc+sBdZz\nP3aOZ3Kn4abW5/BPmf+Jc7UD0IiNL6b/P7xBewH77YU4Yo/giD2KxVNTWGimsAsZtJCWj9ljFmKR\n2yrAKa2211e0ZnQtdQGh6Xobf/6fO3xtRkgSJzouezpMuqIY2FAQ35+usdii/aFJshDLeGCzEBMC\n5NMaGlSB7fIdYF3PeTjraqOQ0TFRa/sssGx/tv6zyIXYmYvtt5qH8MTGdIf1o/QOTNRx9V//Av/v\ney/s8B1yUYIEHfTbPbUfHxD78QF4rsqJ3pssW00Sp7kqJ5V0VNNShUROapEosAm6QoWHfBw/ey8G\n1qPR1SooGWbFfLGbRLQkxJxVz22HsJ26ihoCKx+LLjmcOn3EFj8bwHGM4ObWZ3H38FewrOEk43mL\n/qyf2FbgvQCQA07Yg5ianoe96SEctUdx2B7FUTiKbtpYAjTWwGa0hLAY2IWDWRybCc9eF4xhFfTh\nY2A7F33zF/tw98Yj/usJieBCLF4r/thVzplzoVZVGgMrieH08yDeV7qknRnEB8P0rNNODKyOmiAG\nluXLO/a/+PCBs8DONA1hpl92jiILbNSXUlGSiAneewAAjs00MdNod+gkGmyCBAlOUSQ/XwkSKEWi\nwMZEqVSak3RUgq0v5cXAhit1LKgLsWnbyKTTaFvBONIgxJTPXTTgO/aUzd5diGXDsO6ev/36Zfjm\nL/YJr/diXLuN7bmcusokcR7qH9xxAgAwhRK+fvpf453bP4Vr9E2h1OaRacwzp7FcVI6uBuCrwK16\nAW/NDOGwPYozH1mJj6csrD28CtqutVhL9uOoPYpP/MYVuO7chfjvP3pBIAP2s9+FVOSKbdmAKDRI\npKtks9mQOrB+BVM0HgtLoJ2HuhALLLBhEG6ZLi7EPNqWhTRxhKMRgnxGZyywnHs2d21YfKrjQmwj\nn6EuxIawjE42l3c/i2JgRdZUfwyzdGpdTLBBftm/CfoHhmGg2Wyi3W675RiKxaLbDjj3Adu2Ua/X\nAQD5vLOv+ONyuQzA+Z6nUilUq1X3OJ1Oo1KpAAAymQwymQyq1Sps20Y6nUY2m0WtVoPVcbtvNpuo\n1+swTRO6riOfz6PRaMAwDGiahkKh4PJNCEGxWESr1XKtEaVSCYQQl6c4cyKEoFarod1uo1KpzGpO\nqVTKrateLpdjz4muU7vddq+NMyd2ndrtNsrlcuw50XUyTRPNZjP2nNh1onKKOye6ToQQNJvN2HPS\ndd31ZLFtGxMTE7HnRI9TqRRqtVrsOdF1ojKKMyd+72UyGUxPT8eeE10nupfizolfp/Hx8dhzousE\nAOPj47HnxM5B13X3NyXunKrVKtrtNqanp2PPiV0nug/izoldp1qtFntO7DpFrU2bKLAx0W63kc1m\n5xyd8IfO3p4gDUEMrIsoMbDUhdiyYVsWSOdhvpuiITp/zgK/gk8ftLslUhKhmxhs2+YISJSuLmP7\nkzh5in/btPHYi+Nu/zop4EPtT+IiYw+WkSNYRCawiIzjNDKOCwaryNSOYsQah066r1/GrGG5VsNy\nHAZe3IKPpgDsdv79tLO97PVp4JGF+EJ9ELvSAzhij7r/zmicDUwOAaVFoTVd3XaAs8DK3ZZN05Qm\nwqDWwoBVnBuWnneTOIHg4V0n8OLxKt6+dpGQNnsd8fEq7yviX5bEyaXNcW9aNqjnu+NCrON4RWz1\n5l+G6Ny+YWHZjmtyniZxqhtCJZH9/oqzEAtZCSBSEjGmD88zXaskBrb/kEqlkM1mkc1mAy9R+WP+\noYQ/Hhsb8x3nmCRiAAL3N9lxpVJxeYpzPUW73Z71nPL5PCqVintd3DmxYOUUZ46lUgmVSsXlJc6c\nWJRKJR+NuHKfzbqJXuCzcup1TlQ2KvZSKu38ZhNdw8jISOw50eNKpYJCoRB7Tixmu5coKpUKBgYG\nuvbv9n2yLMvX1uuceJ5GR0cjzyHsmNKJMyd2DpZlYXh42He+lznRY/Y3RfXv3Gx+y+nfOHOKg0SB\njYlms6nE6tlvdESIm8SpzfjW95qxFADS1AJrdWJgda2rG6GM1UJGZHaM5tosTMgjGMxm/rLKiCwu\ns5sLJgEbyyjv58iE4Hl7BZ63V7jtukbwO6uX4aFdJ7DryBTmYQqvX9BE9cQBLCITOI2MY2FH0V2q\nT2KJPgFiNMKZAkCsNjD9MlYBWMWL9RCAbzgfP5AeweWZIexvLccT+mvRMq/08w1HKZGV0eFhGoa7\nJ6S8MbTCenpu6cBPXjiCJ/eO4+1rF4bSZmmGv0QhwtE1jYSuOb/PDNNGWqcvWghyac3NQtzNPTvM\nhdiJPbaFLsTs96vZ9L6/Yhfi4Bi+lxb0ryDeOMwFO+D2bfv/JkgQhn67p57Me3NcqOQpkVM43N8v\nRS4kc1VOKumopqUKiZzUIlFgE0TGbH5+eUUxShIknSkFQjoao98pVQzZ2X//vcvw1+u349F909I4\nVhEix+8yD9o+pZX7TOnJ3JfdGrVM0h/X+iS4RHZfJPASJZnQcRSj2JMZxAvWaYG+Z44VcN8fXIHv\nPbQRd214BqeRcfzpVYP46WPP4m2nW1iVn8aO3btwGhnHMKlKRcAi357A+doEzjf34Xrzv4AXgf+W\nWYbHrNV4zFqDtLHYSeLEGFW7KSnd6sAGT4sJUqueRoCWYWKmaURyIabyD1PA5LyJC8nItlfbspFl\n+Cykda8OLG9Z5mhQOYle+Ni2wz1NbOZkIXbOWRJllLqs+8YUsy2FY5kWK9Z+13P/uSQLcYIECU5d\nRHlqSZAgQa9IFNiY6Ld6TrOlE55bJp4Jlncj6BUpV4F1XNWMCJaYsBjI1acN4pyFA3h037TbFikG\nljsO97IOusCy8vN9jiBWPgZWPKb8Wj5bbuhaEoJmegg77DOwwz4Dty6/GH/z8NkorFqJs684A2//\n/M8AADv+9EqQmSP4q399GMcO7etYch2L7qrCDM5MTwLVYyCCrIurtZewWnsJv417Yf3iq7gqsxKP\nmqtxn7YKz1grYUO+ZzLZDErZ8J8sdnZhLx68MjoETcNCo20J4zw9usT3NywLcZgLcS9ldNgsxI4F\n1iuj080G6yWbCoKW0aEKYaVhCJXETDbocsYiah3gXh/c+JcDogRTCRLI0C/3VNV0VKIf60jOdTlp\nSR3YV4yOalqqkMhJLU4JBbYfE0W0222MjIzMOlHE9PS0y8NsEkXU63UMDw/HnlO94dA0TS8BAp1T\nq+3wW63W0Gw2IycgmJyadNeQyt00nAfwmZkZlMuadJ0AoNXs8GQ5STkMm8AyLZimCRnoelB+p6am\nfIHtjUaj06+Bcrnsq1XLolGvuzyzsYC2ZXeusQMKx9T0NE44l8Boe9dYpve53W7Dsiw0Gg1UZyq+\n6x2ZpN3xjHYbzQ6/7XYbExMTaDWDMZDNkDTotXrNN0dDMl/LslCpVFCt1ty2et0Zu1arukH5AFCe\nriOfX4StmfPxqLXUR+faeUO4/fqzkU3ruPvJbXjgsSfxzvwWrLW2Y429Czo8JVGDiRWtbViBbfhv\nGaBpp7C5sQrNB96ERePnIIVhGMxPVLvVRk4XazFU3q12y10327bRbLXd40Kh4O6NVqe/ZVmo1B2Z\nHpus8GQZWdRQqVTc78f4xATqtbawb7PZxOTERKDdNAzh6wP6faXfAYrJ6RlkNce1Z2pqCjBbqLdM\nVCoVtFr+dWw2vP0KAO3OPqnV66jXdV9SBYt+nzoa4WSt5e6hRuf7Xa1WMTk1JZUHANidFxTNZhNT\n7RoMw8DUtLc/K5UZjI9nYHTKaU1NTaKccs43Wy1fghxWcTYM//e70ejMpVYHcq98oogEpxZkv3Gn\nOh2VUMlTIqdweCEQat7AzVU5qaSjmpYqJHJSi1NCge3HRBE0695sA6h1XQ/wFCepQrlcnlWiiHzu\nRIcfZ0uwPGXSGQBAsViIPOdSqYTsUc/VlNLT9AMAgMHBgdAkCwAwxMghldKR0tIgWguaLo5nBYBi\noQBdb7s0h4aGfDzqqYMAHBmNjY0hk9kvpJMvFFz+Mge8h3KiEWi6LrTuDQwMYHTUuSadSXu8p72v\nmZZKQTMM5HI5DA0NBq4fGxtDOuXIKJNJo1hwFHpNT2FkZATZ7OHAuKmU+GusEYJcLg9d99YhnRb3\ntUFQKpV865DpyKxULPraqVxSevCNciqdcc83CovxmLUW46nVmCEFvP70DI5t2YArta24UtuCNdpL\nrlM4AGSJgYvtLcDTW/A7AN6XzeIp61zX5Rj2YowNiC20VMa5bNYdnxCCTDrt22d075DOX13XXJW6\nBfm+KhQKKJVKSKeclzLDwyM41hIrvLlcDqOjI4H2bCYDXQvGGJc6b0ALBT7xQQF6Z21HhocxOthE\nwziGQqHo21OA8xvg+z7lnd+AbDaHfD7vezFkA0inMzA7Fudqy0Iq5ezXdDqDbDaLgzMGnjjgV6h5\n6LoGwEQmm8FQwfmNmLS8vVYslTA6Ogr9kPN9HB4exthYCYQ447D8st8nnft+pzq/P9nO79ornSgi\nwamFfosz68cYs36MoZurcqJ3OCuJgX3F6KimpQqJnNTilFBgE/QHen2BGNf1mIKNd6RJk2zbDn2T\n6XchDT8v6xO8SJQ5VnyhqEwQ25e1NHUbmo0ZtASuyR5NyfXEORdl2cSupnTM8Fhd0TUimi2tiIes\n1+Ah6zUAgD+7bgEmtj2EM2eexdrmCzhHO+jrXyRNXKu/gGt1p1xP46kBvDTwWuj6mXjMWoPd9hIE\nXGdD5ujj0/LkSeNKp+ryN5FuGR13gG77UJDEichlKYLhcyF26sACQMOwusbAam4MbJCuU77IhtFJ\nzDTdMJDtxMPSvfT2v3u8K3+sOzVLW97f/xcA2qaFNPciJDQGdnY/KQkSJEjwiiIJ3U+Q4OQgUWBj\nQpX7Wb/RESFuFuJcbnYWjxSTcTadSqFtR2Mk7IZB659RqIyBtZlzslhcljfp0MTrwGchFl0iS25D\nBNzK5uvWbGVoCUql+ukLToTVgeXRTA3hl7mrcE/7UuyeqWI+JvCO0i58bs1xzGz7OYZbfmtzzpjB\nqokNuC29AQBw3B7CY9YaPGatQdl4HYB8YH6ySFG2jA6NfZ2ui12CaT/2b7c4bOHLE0kdWDdpFydp\nR4H1XiLQrMGNthmIE+WvpUeiZFP0pQZ1IXaUSHnSJ4olwzkcnPQsyN2yaHukBImkYOMnLxzGJ/5t\nCx74wyu5fcfHwDL0EgU2QRf02z21H13VVfKUyCkatG4/mBExl+XUj/tSJRI5qUWiwMaEqniGfqMT\nOkav/SXWHyDac2hakPSAVRKFIMKPAZ7C6o3y14qVDjFtT9HkrMcdeBmVoynPgSzEAkiTCRHi40nG\nt4xWWOZjWbPIAmvD4UEsM9tVhI5jBPfrV+PT77gaX0/vwr2PPoUrtS2df1uxgEz6rp1PpvAu/TG8\nS38MmPw2Xs7OQ23bldCKb4O17OrQubIWWFeBbUS3wIbtQ9mwuhZtzSkM03KVN40A+U4pqHrb7G6B\ndfdNkK7daacKLE3qJOsPAKsWlvChy0/HZ36yjRlTkMQpZD5sdm3YwL1bjgIAdh7zu2LzNEyXz8SU\nkaA7+u2e+krcm3uFSp4SOXWhQbMQK5reXJWTSjqqaalCIie1SBTYmKjX60reXPQLnbhW1jA0BQmH\nvPG6D5hJeX1M0wTRNewfr+OBbcfkdN3iMWLQhEa0RzQLLNcnwvfdX0aHcSFmNIQodWC9LMRyd97Q\nGrHgsxBL+glfNtBrenEhDl5PLWciS7Zl+99Ms3y8bC/Av5gL8C/mGwHY+NLlFtaY23Dw+QdwhbY1\nUM5nKTkBHL4b+I+7AQB3YzHKB14Hbfs7YZ3xeqDgFTU3Gd282UkaNBVqgeV472KBFUEj4XVg+UEM\ny3bXXSME+bTzQofWgg3jr5sLMRgXYptxh5YpiSOFdOC7wh62TQvf2LAXS0aCMcoBZTvAO/HtUb6/\nySjaCRJ0Q7/cU1XTUQmVPCVyCodbosySZ7nvBXNVTirpqKalComc1EJNXu8EpzxOxksYocWth+tp\nzB+lRckdngpTjHvjKYpXjyyWNqiQ2UJFk73eYsL4pLGlzHVhljSPpneSpaiRYMywTD6it8RUcZDJ\nSNQue5snr5tq+xQj1wVboOZMFc7E+OoP4ffbf4TXNL+F65u344vt9+Pn5kWoCcrvLCeHcNmJf0f6\n329F9m/PRfof34T3Tn4Lb9SeQ8F0rH6EELQ6FtiZUAsstR52mw98/fi2sBc3/Bm/C7H3fai3BQ9C\nkn0tcyFmLbB2BAvsSCETWG/Wvf2OB3bj6xv24h8ffck9b3N/WYRLz382scDKMTExgfe///1YvHgx\n1q5dizvvvFPYb3JyEr/3e7+HFStWYMWKFfjSl77kO//kk0/iTW96E5YuXYorr7wSjz/ePQY6QYIE\n3ZH8aiVIcHKQWGBjYrY1TvuVjghxjbNhWT+j0MwzCmxKT0FFsm+asbeLd6wPbB/bDlddRM/YvuuZ\nz7xCcMESf1ZiAlZJkLtes0oHrf3qfCY+99AgN2IaLq89uFmL6LAxsIZlB2KAqOIkixHmkc5kMJDr\nrB80bLHPxBbzTPyDeT3OHc6icGITPrv6GC40NoK8/BSI6X/RoR3djHdgM96RAawWwY7MUhyYvgD3\nm2fhcZyDqfp8+eB0zoSxbEp4JZ3/eOgSC6xMvoZpo90xFad1zR8DG7Bq+onoLJ8caBInStuyvRcv\nshcQ69YsCNTJZcfcfMiprdwIq6XLuGHzw7DH/F40GUU7gR8f//jHkclksHPnTmzatAk333wz1q5d\ni/POO8/X79Of/jTq9To2btyI48eP413vehdOP/10fOADH8DExATe85734Ktf/SpuuOEG3HXXXXjP\ne96DF154AcPDw6/SzOKj3+6pJ/PeHBcqeUrkFA1EUR3YuSynftyXKpHISS0SC2wCANFciF9pX/lc\nmtmeEbXBZ8V/AAAgAElEQVRof+xq8CK+SWoR87kAi88Hmm1ZEifGFZp5OqftpYyOHV94M84YLfja\nnaQ/nAW2i9XTN//OXyuKBZa6+zJamZfEKboLscmM5VrgbILJWhsjBX8CLbszrt8CG77HBnPid24t\nW8ez9kpsWf47aL/v39D6o524FZ/DhoUfgrXkEtjEX5pFg43ztAN4a+0e/LX293g094f4i33vxd+l\nv4YP6fdhDdkHDUFljHIaHusplrNGwvNy89cYlo1623EXzqY09/tQFyVxkuxr0VeWT+LExkmLrJzf\nv+VirFuzUOpCbDPcHJ1mygTZXRRPSXvAhbiLe/OvKqrVKu6++2585jOfQalUwhVXXIF169bhxz/+\ncaDv+vXr8Yd/+IcoFApYtmwZPvjBD+IHP/gBAMf6unDhQvz6r/86dF3HzTffjHnz5uHuu+9+paeU\nIMHcQ7ffwQQJEsRCYoGNiX7zZT+pfuwxTbAtQQxsLz/irAuxZZogWjqktwOauEiGdttvx42WVMfv\n4ip3kxVbSnkLLn0TS61xYVmEu/Vxzkm47rgQ+5RmCQ2RC3FY6R5Ru64Rn2zox5oJtE0b84oZAe+2\nay3sMCKF0W67FtggHa4hnccvsRaLF70Fl79jFdCsQDvwBO6/919x+vSzWK29hBSnoI5ZJ3CDfgI3\n6E8AAGbsPJ6zVuBpaxWWTr0RaM335hyyHiL3csDvEs73F87XstwSP7m07paVMpnyOjIatDINv2/Y\nbNNuDCxjgRXtJSpz3nrMvsCgw1Crrgh+TwR5P/6clbgQC7F7926kUimsWLHCbTv//PPxyCOPCPv7\nv5s2tm7dKjxHj7dt24ZumJ6exoYNG3plXYj169croTPXkcgpGvpFThuPEQA6KpVK3/BE0W/89CsS\nOUWDKjldf/31kfolCmyCVxTuY1IEvZHWpnQviRKvKvnM06APyXGTV0nrwLrjyGNgIejjpx0cJ8zl\n2fdgTzwmCCGdREneeanCLrHUhYGXgUY4F+IO0ZmWczxa8iuwTnwuIPKskrE5kBX/ZLnxunztYIps\nCdaKN+NHw2N45EQZp+UMnNXajuuHXsLplY14rbYLJdLw0RwgdVyjb8I1+iZg012wN+t46+AqVFPL\nUHxxEun0GjGTEK+trhG5xR9BeRqm7SaYyqU0V9E3BW7sUgss149NrCXKQix6OcPH/1KwMbAi5dKL\ngeWtxeFfOmkSJzU5UOYMqtUqBgYGfG2Dg4OoVCqBvm9+85vx1a9+Fd/4xjdw/PhxfP/730e9XgcA\nXHbZZTh8+DDuuusuvOtd78Kdd96JvXv3uufDMDg4iHXr1s16LuvXr1dCBwDK5TLGxsbmHB1AnZxU\n8pTIKRy15w4Be7aiUChg3brX9wVPwNz+zqmklcgpGlTKKSoSBTYm+s2XXRUdlW7CYTGwUZDWPc3G\nqQMb4aIuCmk65Vhx6TR7TeJk23IlnI2LlCnSfmWy0yYd2OtjhmiTfhdiT4MlcBQTkxmgm/7KjtI1\nBjag0BB/GZ3Ox4rhdBRZYG3Y0IjGHMuRTqeR0jUsGsziyLTfuu9ai0OuZ89XkMNj1lqUM5djR/t6\n6DBxSe4gzm1vw6XaDlyi7cAiMuG/1jYxOrUVt6a2Ag/ci9MAPJRZiGfslXjKWoWnrFV40T5N7F6O\nCFmIOZiWjUbbqdGqacS1wFqWKLOvLAaWs2YyllaDiYG1mfYg350xeBfi6FMJXO9759LxFBDFxgJe\nxujEAutHsVjEzMyMr216ehqlUinQ9y//8i/xiU98AhdffDFGR0fx7ne/G3fddRcAYHR0FD/84Q/x\n2c9+Fh//+Mdx3XXX4dprr8XixYtfkXmoRr/dU/sxxqwfY+jmupyIojqwc1lO/bgvVSKRk1okCmxM\nRCkDcyrSCUOvz4+z5Ym1wBICEAXPr1FjYKNaclmwsYCyMjq27dFzraEyF2AA73/d6dhzoorfvfpM\nKb+ydaGKgSxLsZAGQ8t0FVjxVaKstCwvPFujnALrWIe5GNiQNab9Nvzx1fj8f2zDPz99MHCdP/ZY\nTou+EKCJiUzoeLJxBp7EGfjf5tsA2FhKTuAS4iizbx/ch7HangCdM7WjOBNH8Zv6LwAAE3YJJ3Ze\nhFzmGlxM0thkn40W0i4/4uzEYgtn27LQNCzXlZ7O37HAhvsQs9ZRFhajDLYtWkaHVWyDC0DHlbkQ\n24Jx2LFF7s7Mu55gO3dBUkZHjBUrVsAwDOzZswfLly8HAGzevDmQwAkARkZG8O1vf9s9vu2223Dx\nxRe7x1dddRUefPBBAIBhGLjooovw0Y9+9CTP4OSg3+6pr8S9uVeo5CmRUzjswIfZYa7KSSUd1bRU\nIZGTWiQKbEzUajUlby76jY4I4aln5Gg0GsHGiJYyAMgwCqxpGLCjxMAi/D7Rbju1Pl1X3wh88N/v\nMCXLEmhSfhdiO9DOKw1etlaCUjaFL//GWu+ccEwIz9P6mqbfb1nIt6zcimxM0RlN81tgeZLzSgIL\nrO1XjMJiI1utlvScTNmWeRRQPhudJEkpjbgutQ4IXrbn42V7Pv6PdRUql56DW14zhF8+ej82Pn4/\nbll6GNljL0C3/DyNkApGJh8BHnkE/5oFmnYaG+2z8LS1CkPTV2GvvUw6B5ZzjTgW0kbbdJM3eRZY\ngZsvf+wm/5LLk1pg2TI6UV4gsDxSWLaNeaUMTlTka0S7d7tf8ix4WYgTDZZFsVjEDTfcgNtvvx1f\n+9rXsGnTJtx777247777An337t2LoaEhDA0N4ec//zm++93v4p577nHPv/DCC1i9ejXq9Tpuv/12\nLFmyBNddd90rOR1l6Ld76sm8N8eFSp4SOYXD825REwMxV+Wkko5qWqqQyEktEgU2AYD4Smrs8SK8\n9ckwLsS6RtAwu98AZLGnsnGjJHFiZcMmaeKvZLO5yiy4bJZePr41OG408Erx+j+4AimN4D3feRrg\n4hNlNF0FhlEfenUh1gnxuSuztAgBhvNcFmLbGUPXiK8tjE+Pnr8HVep4BV4GqhTRsi9jpQyOTofU\nFwaA/DCOLrgGf2WM4k03XIH9xybxrX/5CS7RduASbScu0XZglPjjD7OkjUvJTlyq7QRe/A+8D8DO\nzBI8ba3C09ZKPGWvAhFsgJSuOS7EhoVcyrHAUjkZNI2wTx7+Y68OrB+spdWLgWVdiEUWWNkY3v61\nEYxZF7mlu+e4RhudNbXtYBmdEPfmX3Xccccd+MhHPoJzzjkHo6OjuOOOO3Deeefhsccew0033YSD\nBx0vheeffx6f+tSnMDU1heXLl+Pb3/62z1L7ta99DQ888AAA4LrrrsP3v//9V2U+CRLMNSTv3RIk\nODlIFNiYmG18Z7/SUYlMJmhx6wXsA3Exl8b4VLvrNQThlhpd72Q27nTpNQbWuVRM32bOsdfwLrL0\nUKZkhLEkdF3mDKxnzSu6n3kLrHS+AgtcNwtswIVYkoUYAEYKTvwqD8u2uTI6cuRz8v1ElZxoWaW9\nuTU7Fth5xXAFlgre9fq2AVvP4Fl7JZ41V+J/mQ73y8kh/Mm543hj4UUc2vQQztKOBkit1A5ipXYQ\n78PPAQDG92/HQHopVuZOw2iqiRpyMPQcFo2PoEmyWGZr0LYex0BDwxXaXoyMG1hmTmGGGKjbWdSR\ngca93WeVS9G8ndhoTzFk24NTpy7EhGtn6dpy2XMvQqjjMZ+xm7jd/UwkWYjlGBkZwQ9/+MNA+5VX\nXukqrwBw44034sYbb5TS+c53vnNS+Hs10G/31H68N6vkKZFTVKipWjmX5dSP+1IlEjmpxSmhwBqG\ngWaziXa7jWanNEuxWHTbAaBQKMC2bTdzIjWJ88flchmAs2ipVArVatU9TqfTbgbHTCaDTCaDarUK\n27aRTqeRzWZRq9VgWRYsy0I6nUa9XodpmtB1Hfl8Ho1GA4ZhQNM0FAoFl29CCIrFIlqtlusKWSqV\n0Gw2ZzUnQghqtZpLM+6cKE3DNF050TlR2tVazeU3bE50nWq1qruGVO60dMf09DTKZfk6AcDMFJNE\nxzRQqYcoGB3UazWYnTnUajVMTU0hl8u562R0XIjrjQbK5TLabbHLY6Ne93hue4qzZdswTVOoJFdm\nZjA+7nxuM9cYhle6xzCdvdNoNDA9PQXAeWBvNpvuOrU7/dvtFsrlsm+dRG7ZbYa+bQMTExNOSSXb\nRr3e8CmwLF8sLNtGpVLxZR6tNxx5V6tV1Go1t71cLiOfz7typiAAWm0D5XIZ2WzWN++hrO7ua1Yu\nhmHCMBj5WhbK5TIazeA8M5qzb5z95T9vdvZVs9lw1822bbTabfe4UCi4PFOliJapGcyGK761WhWV\nSsXdC5OTk6jVTa4XwR57CZ4avAQrX7sAb3rmXZiHKVys7cCl2g6sG9iLRfVdSMF/Xap+HKfVj+O0\n6edwHvuLPM58/gmwGMCPMgCeAN4CAOx953HA/mUGz2fTqCGL3C+LuDqjY/EDw9BKgzC0NOxUAelU\nAZ9NTSM/XcDVuo46ssi2i2gbOZytEZw1uQDGi+NYTfahhRQ02NCPbsTMuIXUwUlcQA5Agw0NFk5v\npTFCGtD2mTi/8SJahomztSYILGiwMfbSflStIhYdqeEd2kFoG/ejltdxA9mHNUdLWDDTwEK9htN2\nbcXNOARoNkAsnDOZw1l6FVqHzsX7B/ARfRLLj2ewqlZFa6sJ86w3uXsy7m/5SSs7luBVRSql5rGm\n3+iohEqeEjlFhCInt7ksp37clyqRyEktTgnOU6kUstksstlsIMMif8w/lPDHfLroXC7nO+bfRsiO\n6UN61P6y40qlEuCp1znl83mUy2X3ujhzyuedh3xqoWR5ymYdy1chX4g851KphPRxT+mh9HT9JQDA\n0OCgbwzRw+SC+fO889kUoHXfroViAbrujFssFDA0NOTjUdMOAwByuSzGxsaQywYtZACQLxRc/tLH\nj7nthBDomu4r10JRLA1gZGTEGY+xPqfTjOssIdA0DblcDiPDwwA67peMXNOpl10a/nXIIp8L8qvp\nXr1cQuDyoGkaMtmsz6qWDbGKl0ol5JgXCJTvgYGSb31cuXA/fLpGoOm6e17TvfOFbDqwT1KpFIiu\nI5f1eCKEdNbFnwEYAHRiYXBwEACQyx73n+yY9/K5nDs+0QjS6bRPhlRWvHvr4pESsG86MCZFsVBE\nqVRCJuMoRUNDQ5iyxGVGCvk8xsZGAQAnMIT7rMtwn3UZTpx/JrbsOwrj5adxMdmJS7UdeK22CwOk\ne7mSKCBmC8OkhWFUgcY4RjU4SvA4wDpv35oC0IbXSN8zZAAcBvBj4D/ZpfqJ8+ctAN7CtjfgKNH3\nAP+TtrHba5vz7w0A3pAB8LjT/GUNADUOpgFsAi7Umeum4Gf4MPCmNIAZ559xcB7M1dcH4nZ6/d1L\nMDdRrVYDe2Eu0FEJlTwlcgoHfddtKaoDNlflpJKOalqqkMhJLU4JBTbBqwuV0bFxvQCzKQ0tI0IM\nbI90e4+BDbaxEMbAskmKbDuQhZh32/Sy0gbHELX5Y1yZGGA4Ls2BOrEivjn+Wb5kcxXFRPpciBmH\n4Ewq6D5ld4KGhVmIBUNmBS7IFNTKHEzixPEsuV6UYMp3nXshdYANh2gcjRC09RyesNbgcawBTECD\nhQffP4Jjz/wnJtNjeHjrfuTRxMKciYV5C5pRR0lr4vVnFNCqV/D8i0ewYoSgWpmBbtSRJ03k0USB\ntDopu+Y+iKJkKAkSJEhwshGWmDBBggTxkSiwMdFvvuyq6KhUVjNpUd3Pzjg9DlTKZdCKmMQp7HaR\n6iTECVOUgjT9x/JLbSYG1q9IUkSKR+0RfAysR98JgmXHlIbACt4sWFzsIg9esdUIp4wzn9MS5dOy\nAT2iHAYK3h7neXKVbaa9F/F2VWC5cdmEXaLOohcNGgm+MLGgoT1vDQ6NlHGgdC7+adNuAMCZuQIW\nlLKYqrexdCSP1914ISYqLbz3rx7G5y5ZhX9+5iB2HvUSRv3xdcvxu1cswuVfvBd5tPDxaxfjHzds\nx+ffegYuWpgG2jWgXUO9WsHX7t+M+TkTVrOKHFoYS7dR1FqwWjWcUbJxzoiGHS8fQwYGLGhYNq+E\nVEpHpWVj33gDVsdJOJdOo9K2cMHSEWw/WoVNNMw0LVjQYIFg5aJBnDZcwKHpFjYequCalQtQyKTx\nn1uP44zRIqabFg5Nt/H6FfPwyIsTjiws4LThAg5MtjrjEKxZPIwXDs3gjNEizinUsfzsN0Va0wS/\nmui3e2o/Wv77MYZursrJK0yg5oY/V+Wkko5qWqqQyEktEgU2JnxuoXOIjuiZ/LevOhPPHZjCm8+b\n3yNP6rZXIZuOZIH1QXDD0DkXUpkFVpZFOEwBZ8uRyOqRWrbXoOqGJktuQ4iT3MjqJI5yEkiJxxRn\nIe7QkYwbyEKsEV+WZZYroQUWTPZZwTU8CmFJnCyaxCk4RhR0t8DSREbd6cqTXpHQlxbsKaesT6cO\nbEd2WkeEpkB7JhoB0nlMYBATACoDZ2Oz3cLEvItgLfdc8Wu1Fv7h3ocxijTGO7HH8/MZZHQNB6sN\nXL9kIb5y0/l4++d/5l6z4T1XYdFQDs/sKeOW7z3ntq+ZN4Ath2aw4devwid+8DwyuobNhzw37C++\n5jzcdPESPPLcIXzqpa34r7e8HktH8vjk1gfx7mWLsbdcw8PjZXzr4ovw2V0vOJnGDQtXD4/hFyfK\nLp0PnnY6/mn/AbxhaAy/Me8ozlrxFrkQE/zKo9/uqaroqIRKnhI5RYWa+/1cllM/7kuVSOSkFmrS\nov0KgiYImWt0RDhzrIB7PnoFRou9ZRVmE//MFrbRimSBBcLdlNtcLdFoWYhZF9dwlUik9GmS67vp\nr1H12zAPYSoynSrNXYl5H7tZYIN1QYnLy2N7yrh742H3XEZiZrU6ZXQe/ZOr8d5Ll4bK12x5iZt4\nai6vrAt1D88LY132tpcpl2b3lfMZJi/hCwSRtVZzZNlom8jSOrDU5TxCHVg3CzHXTtlud2rApjrj\nuHFawizE9G9wvekYtm0jJfkyRc2y7WYh5trZbMkJEnRDv91TT+a9OS5U8pTIKRz0Z0tVDOxclZNK\nOqppqUIiJ7VILLAJXlHwpTOiIhM1BrZHwlG6831k7sc283+ZKyv7EC61/rrlRkQxsMH+MmWKEOJZ\nJjv+vfJKJyIXYpeSmD53rGvEVSRZSx0gdiGmihMBMK+URUYnjHt2cEy+zqiI14C7d8Sg65FCl5cz\nrhJH6YbHNonkrJHw/ckqiFQXZOvA0sRhpi1QCiUlbljr/PGZpttOv0uZlAbL9uKkRXPirc88j4Aj\nD12mwApehLCjeO7ZjHAZUKt+1LVMkCBBgn5B8rOVIMHJQaLAxsRsa5z2Gx1F3qw+hPHUq/tsKZdR\nksTJdSHuJS6lB0uoMMmTz4WYTeLUZViRsU7Qj1WK+dhbs/PWl44ljYHl/gKepU8qIq6dEED2klnk\nQgx0kloxLtVhN/uBvDxWwxTwKlKCZeSHC+FuNJSWZyUMUV4laa80jQhfWgj7dmTRbJvIcRZY07K7\nJqfi68A+uqeMD3/vOfz5DecBgOvNkNE1Xx1YkfwDCqbb7o1hA+DfUcjWkq6z7DxvaU0ssP2Lfixx\n12q10Gw2Z13izjAMl6fZlLir1+uoVCqzmlMqlXIzhbIl7nqdE12ner3uXhtnTuw61Tsl5+LOia4T\nLdEXd07sOlE5xZ0TXScqn7hz0nUd7U6ohmlZbom7OHOix7Zt+0of9jonuk5URnHmxO89wCtxF2dO\n7DrRMn1x5sSuEwCMj4/HnhNdJ0pnNnOic6BlAuPOia5TvV7H9PR07Dmx69RmSg3GmRO7TrVaLfac\n4pS4SxTYmOgXxVM1HZVQ6Vtfymddt8cwyJInUdCaV1QBuWrFGP7pyQMCOsxn7pxMeZlpGNh2ZEZw\nPetCLOZVhKgqvi8LMXORRoC2GxsaHndrCxSYZueFQVhMJ39sSzLEZkQWWHjxuWHjUJTybBInmVXY\n3x5V58noWjAJFUvX8yF26NIAXklfcRIn4tIRjcVeQYizrg3DQrZjgaUWTtMK7sBARmjN7+q88WUn\nNvWZ/ZMe/wDSOkHbtN1+onhqus78Cxd/bLcNXZO9pKDzk7ux28w+4DmwLDlvCV5d9GOJu2azqaTE\n3fDwcKAtTok7ys9s5sSCL63WKz1af56eizMnFvPnz/eNE1fus1k3fg4AQsv0dZsTXScVeymVcp4J\ndF33yuzFmBM9pjzFnROL2e4lCnY/hfXv9huh67rvul7nFIenKMejo6PS87387vHzA3qbEz0uFotu\n+2znODIyEvj+xv0tp39fqRJ3SQxsTNA3CnONjkrUBTGwcR9BrXYzWhbiLufbbX8M7LUr5+G5z7zR\nPRbF8fljYL02vucX7tmO3/vhC4Lrvc9skiOZBdZ90BeGS3axKnIKMrVeydw7hTQ6qLdNKR8On37o\nRK5kiMvoOOO61mES7iZqMDGwMrDTjGrBpn0vO3NEStfTXzuKYQgPRDIOm4W428sLjRC0TAu2Dc8C\n67oQOwqnb66CsVg+6TG/Pp4LMT0vmI+7PmI3ZRu20IWYV7O7WfJd67bEhTixwCaIgn67p/bjvVkl\nT4mcuoD+tiqsA9tv6Mc9kMjplaf1SiNRYGNCVTxW/9FRQsahpY4UMjpxLYKzgTs/hrlCRnc/pwTJ\nhgIW2AgTk1lwWUuTrL5qr5CV0QE890s3iZNkSLp/WKWj1nIU2G6xuhSaRiB7xyBL4mT76sAyMbCC\n7lHK7QQUw4ibkAD447eskCvrxP+32x6QvXygOp5I0eat5422I0w3CzFVQjsWWN+6SBIseYm4/McU\nad0fAyt6AUEEPAO8Z4EduRwSfVEhE2EwiZM3RoIE3dB/99T+27cqeUrk1IWGAj589OaonFTSUU1L\nFRI5qUWiwMZEv6XD7sdU2OlU0EM97nellM/46pnKEPJMDwBI6Xqwkb2+C31XwerSj1UuZAqg1ALr\ntkeLlwwro2O4SZzCeRG5EFdbhnRMES2dEOmPoayMDhsT7Cg2ksEQbY8Tyedu0AjBBUuGsPVz10no\n+t1fbdhSjwAiyTasE3k8qYgf+gIhm9bdazRCLbDhbu58DCwFz3JGJ7Bs8frztIIu4941Tgxs+Jx4\nKzaFZdkwLBupjps5v4c85TqUfIIEAPrvntqX9+Y+LMMxV+XkJbFT88J6rspJJR3VtFQhkZNaJAps\nTPRbQeJ+LEacFsbldkkMJMFgIRi/IUY4YT0VrsCKqPiypzKWo7CRSARNqmsMrNCKF2wLT+LExcBK\nxhK6ELcsj1AEEEKkSoYoBhagFulw3iii7PHYzwgCK6iYvtPh2f1T+KM7N/c0BFtGx789gm26RtDo\nuHBTF2LaTj3RWIWS55uKm8/OLLLAsu1CC6xkDP/3Iuh+H6YUs03UVb2Y0YX9zSQGNkEP6Ld7aj/e\nm1XylMgpKtQosHNZTv24L1UikZNaRFJgJyYm8P73vx+LFy/G2rVrceeddwr72baNz3/+8zjrrLNw\n1lln4fOf/7zvbfqGDRtwzTXX4PTTT8eFF16I7373u0om8WpAVY3TfqGj5qfVj0aje8xiVJjtZuh5\n+vDcTQEx2k5GQNmjsEipFJHsquiEXE+P5TGw8nFF8Fus2BhbAsPkkziF07DhWEsJgJprgXUuuv9j\nV+I//vvlHp8CpamXGFjY8CVx8nMfBLvH5a6+fBxmNHSzjPKJpjbsPBGRsp83WUIk3yCd82ymYK+d\nuDGwYRZY6jLOl62Sx8DKrZzeyw//KFRW1JIuS+IUmB5naa82HQWWuvIHXYg7ezPRXxNEQL/cU1XT\nUQmVPCVyCgf92bIkCQ57xVyVk0o6qmmpQiIntYiUhfjjH/84MpkMdu7ciU2bNuHmm2/G2rVrcd55\n5/n6ffe738U999yDRx55BIQQ3HjjjVi2bBk+/OEPo91u44Mf/CC+8IUv4Ld+67fw3HPP4YYbbsDF\nF1+M888//6RM7mRCVUB+v9EJKw/SMy1FP9gAkCLhfOXSGiqdB+FQn36794dhXxKnqNdGciHu3QIr\nUmt9MbDc9YabxEl+PVu/1bYd5SmX1gJJnJaN+TPPibMQi+citcDC9inXYXWCo+xxn2IoICJbum5r\nwdOcrLflXSSkdI1NWCW3ntLznvXU6+BYYIMy4hVvmoWYp8G74acDZXSix8AGXMj5MjruXy6Zk9vB\naa82nRcl+bTEAhtiHU6QgEe/3VNV0VEJlTwlcgqHKO/GbDBX5aSSjmpaqpDISS26WmCr1Sruvvtu\nfOYzn0GpVMIVV1yBdevW4cc//nGg749+9CN89KMfxZIlS7B48WJ85CMfwQ9/+EMAjhV3enoaN998\nMwgheO1rX4uVK1dix44d6mf1CiAliO+cC3RUQhRv6pXUkOPO37kU37/lYl9bOp1GOiRLDH347ea5\nq0kUKfea3vSYSOe7JQaaLfwP9rwLMa0DK7fAaiSoBOdSGmqt8DI6Acsy6TELMfyxnN2SWrF7PCpP\nURMUdIud5i2wk7UQBVbSzpbREY7B9RXV4XVjYBF0F2dBLbBWwALr75fWnbhlO8QCS8eRxcCiE5Pb\nLb6a5ZIdptLiLbB+JpI6sAl6Qb/dU/vy3qyQp0RO4fB+/tTc8OeqnFTSUU1LFRI5qUVXznfv3o1U\nKoUVK1a4beeffz4eeeSRQN/t27dj7dq1vn7bt28HACxYsADvfve78YMf/AAf/vCH8cwzz+DAgQO4\n/PLLA3R4TE9PY8OGDZEm1A3r169XQmeuYc9+DYCG3bt24eylauR0qAbQLUbpjY/rAAie+uUvMdHl\n3cX67cAfrAZ2TWt4/PHH8ckLgL/aqKNhBm8ERqsJgODJJ5/AS8eduWzbtg3rJ7f6+u0/SADo2PPi\ni1i/fjdzxuHTKYJO8NTTT2N6l3Pr2TXlXAM4D+OHDh1CtUYAf6krHzZt3Ohes2vXTvczAMzMzGD9\n+r3THP0AACAASURBVPWotoPyAYDDhx3+Dx06hPXrX/bR3feSc45Fvd4AVQ4Mo+3SmqnoHeWBoFmv\nAyA4cuhQ4HpiWwAI1q9fj737NJgmAdFMHJ+YAkDw7LPPork3qD3s2+fnZWpiEs02nYv/p2Xn9q1Y\nP7HF17579x40GgQvHziA9etfwov7NZiWw8eeA8F5Pv7446FyAOBbt1ZDx8svv4z16/e7508cF1/3\nwAMPwA01tZ09ymLz5s0oHduEbZPOXjgxUw/0cee6cwfWV7YHZLBly2YcniIANFidfQYADz30EEay\nwLbt20D3yXj5BEyLACB44fnnQQ50lDhDx959L6FaJbBMuDS2bvPL99lnnwGg44WNG5E9/AJ2HHL4\nPnrsmG/+E3Qcy6F14sSJwPr97IEHkNGBg1X42ssnTgDQsOHhh1Gr6zhyuOajvWXLFqwvb8aWo87Y\nDz30IIYyQLulY//+/Sg3AEDDlu27AWioTJYBaJiYmPTJ9tix4wA0TE5NAVD3G3799dcroZOgvyCq\ndzkX6KiESp4SOUWDqiROc1lO/bgvVSKRk1p0VWCr1SoGBgZ8bYODg6hUKoG+lUoFg4ODgX5OvBbB\nb/7mb+JjH/sYPvnJTwIAvvKVr2Dp0qVdmRwcHMS6deu69uuG9evXK6EDAJOTkxgeHp4zdLb9bDce\nOLgPK845B6jvVCKnZ3YfBl7YAgAuve8fehp7ZiZx2eteF1p3kwed3/PmZvzHxiOB8/l8HhOtBq64\n/Aoc33gYOPoyVq9ejXWvO93Xb8f924D9B3H22Wdh3VvOcduHnn8IU3UD6VQKTdPEZZdeiivOdopX\nj+wdB7Y+6/ZdvPg0jB+aAUHwO0Bx4YUX4p92O0l+Vq1chZ/u95RlZz+/DlP1Nj799AaffADggcom\nPFs+iqVLlmDdujU+uhvv3wUcesnXlslmgU5920w6jXXr3gIA+MbeJ5xSLPUaSqUiTjRrWLJkCZ46\ncdh3fTaTRqth4G1vexuev28XniwfxFAxjYZpA/UmLrn4Yrxh5bzAHDfevwsPHvZ4GRsbxeHmtDP+\n4z/z9X3Nhedj3UWLfe3Lly/Hk+MvY9kZC7Fu3bnY9rPdePDwS1i37i3Y+fM9wMt7fTQuv/xyd48/\nt34nNhzeDx6vu+xSXH6Ws25/sfkXWLJ0DOvWrXbP33nsWWBqPHDd2976VtdKTJ74WcCN9YLzz8e6\n1yxGaXcZ39z2HFqW/GFk1apzse71ywIyuPCC81F7cRzPnDiCTCaNet1xnX3jtdfi+ccfwurzzsO/\n79sJAJg/fz52TJUd2b3mIrxt9UIAwJ+9sAFLT1+Ivc0y2vU2GqZDY83qNVh32VJ3zMsuvQTf3PYc\n1q51+D7y+H78n5d2YnRsHjDpzX/RwgXYPnWCmnYxMjqKdesu8fG+7m2ObHYereDLG59w2+fPn4/t\nU2Vcc801+F97nsHpS8fwy+OH3POrOzxNPPUy8OJ2vPGNb8SCgSxu2/gwTj99PjBRB6bGsWDJ6cDh\ngzhz6WJsnjjirPHMlEtnZGweMDXeuQ9NKvsNTzA3Ua/XlSQm6Tc6KqGSp0ROXdC5mZiKXDXnrJwU\n0lFNSxUSOalFVxfiYrGImZkZX9v09DRKpVKgb6lU8vWdmZlBqVQCIQQ7d+7Erbfeim9+85s4fvw4\nnnjiCfzt3/4t7rvvPgXTeOVhmuacpKMSlhXkKa4XIJ1fl0odXb10aCIFXkF56H9cjWc+da04iROf\nGCjCJML4JG6fcEdYYZ4fQZs0IRU898uwJFc6Fy8JANmU5pZxkWZR5o61MBfi0CzEHkE2mRSPKHu8\nm+u2PHkX+1m0B+Q0w3jw0yDShEg8fHVimb4pjcC0bK5+bpAvvg4sBR8Dm9L8ZXTC3HQDdWCZY76s\nDxAS+wr/OlRb/izEQZ6trrwlSEDRb/fUfrw3q+QpkVM47MCH2WGuykklHdW0VCGRk1p0VWBXrFgB\nwzCwZ88et23z5s2BBE4AcO6552LzZq+0xKZNm3DuuecCALZt24bly5fjuuuug6ZpOOecc/DWt74V\nP/vZzwJ0TgXoXeqJnqp0VELX5Dz16kxD59ftwb8rnU6mVP5eUsjoKOXEDglxRuwWUxnWHjawuIyO\nOIsTIcQro0MVWMEwbMZaSqmQ8RRYuULmP9bCyuhI6sD6kjiBMBkbg4REe/y3rjgD7zx/kY8H3xgc\nGdnLh26x0yTkXKCvpJNGxIowH1/r9BUrp5rmrWl4HVjnr6uYSkrR0O9DWKIkUeIplkfbRkChZsGT\n5LvRJE7FLFVg/edp7dpTueB6glcO/XZP7ct7s0KeEjmFw/3ZUuNBPGflpJKOalqqkMhJLSJZYG+4\n4QbcfvvtqFareOKJJ3Dvvffi5ptvDvR9z3veg69//es4dOgQDh8+jK9//et43/veBwC44IIL8OKL\nL2LDhg2wbRt79+7FfffdhzVr1gTonArI50MCIE9FOop+XFlkc0G3hLjPoHR+UcrXhI0Rp2hz0LLE\nDBbKiYPYWYgjLgr7wO9TfOBlIdZCNDBqgXUyLDvlWQrZNNomVZSi8a8RuZIhs8D6a9iGZ2xk9zg7\nHZ+1MkSpk5DtXCe3ZrKNUeKYZD00Qtw1Fa29jAe2p06cjNG8xTNY0shTLgFvH/DKId9PtHxu7Vre\nAst8tiGYd5jiypbRoRbYbKrDo//CsBI/CRLw6Jt7qmI6KqGSp0RO0aAqBnYuy6kf96VKJHJSi0jp\np+644w585CMfwTnnnIPR0VHccccdOO+88/DYY4/hpptuwsGDBwEAt9xyC/bt24crr7wSAPChD30I\nt9xyCwDgrLPOwt///d/jk5/8JA4cOIDBwUHcdNNN+NCHPnSSpnZy0Wg0lPiN9xsdlWi1WoE2auPr\n9beczk92nWs77KLAOEma5BCT97daXA1O4RVhfHQapHVgQ92PgyelliniuYxSK6tIcUpxSgwBkGH0\nzW71at3jXi2wruUuSE9ER7THCeHl5eeq2jLQNi2kOwq0TFZdXdPDT0eCRghjzQyn7rfAMi9DqAsx\nOBdijgbvQkz3gciFmEWYBZbfO7wLsUxIIldiG95+o3VgSx0FlufRlFiPE7z6MAwDzWYT7XYbzaZT\nq7tYLLrtAFAoFGDbNur1OgDvgYk/LpedmO9sNotUKoVqteoep9NpN+9GJpNBJpNBtVqFbdtIp9PI\nZrOo1WqwLAuNRgPz5s1DvV6HaZrQdR35fB6NRgOGYUDTNBQKBZdvQgiKxSJarZZ7zyqVShgfH0cm\nk4k9J0IIarUaqtUqRkdHZzWnVCrlJlspl8ux50TXqVqtYsGCBbHnxK7TsWPHUCwWY8+JrlO9Xsf8\n+fNjz4ldJyqnuHOi69RqtTA6Ohp7Trquo93hxzBMTExMxJ4TPTZNE6VSKfac6DpRGcWZE7/3DMNA\nNpuNPSe6TidOnECxWIw9J3ad6D6POye6TgAwPj4ee07sHGZmZtysv3HmRNfpv7YdwYKRIVy+fF6s\nObHrVC6X3eeqOHNi16lWq8WeE7tOhYK/ZKMMkRTYkZERtxwOiyuvvNJVXgHnQeu2227DbbfdJqRz\n44034sYbb4zEWL+jmyJ0qtJRCVMhT3R+3aySrBuqCLTmlVTni+C2G+U52ueSGlEBjMKLCH4PYu9A\nIwQGLaMToqHpzDl6dVZnlSMZg/5DjQSVD4p0iAVWpFSzSs+vXbAIt75+GQzDeyHiXUJ8e4K3xq7f\ncgyV5gv4zgdfI5tFpy+vMIrnEWlNpBbr8HJGfkurmJxOgqVxRPT4uGbDjSPlXYh5BVbAl/vyQ9xu\nd+hG9ijgXYhbzne71HEhDiiwiQW2b5FKpZDNZpHNZgN5Mfhj/qGEPx4bG/Md89kx+ZdXsmP6QBa1\nv+w4k8kEeOp1TvQBj14Xd04sWJ7izJHnJe6cKIrF4qx5Ama3bqKcLCxPvc6JfVkw272k65MAnN/L\nkZGR2HOix1QxjzsnFirWjfLEJnCV9e/2G8HvpV7nxI5JXz5EnUPYMaUTZ07sHOr1euA3pZc50eM/\nvf9ZAIew4wtvnvXvXDabDeyDuL/l9G+cOcVBVxfiBGJomhrR9RsdlUYOVTyxtHqxfArpuB0kCopA\nXRN6lEraRXzI+slcikK8fbvHwHJ1YA3OAiuC50ZKXVMJcmlv7SK7EDN0eGRSYiWVuiw748C9nlVW\n3rF2Ic5dNCDcT7wFVsTqI7vLzJjxIIpTlfaVtLN1YLspe+wLB8K1mxbcdZJeT/xrQfcBdQuniGKB\nFfHhjOF9Fhlgw5KXsHuk2jSRSWmuld5ILLAJZoF+u6eqvA+qwsm4N/cLHZVQwZMbAqvGg3jOykkl\nHdW0VCHhSS1OXc5fZUQ1cZ9qdFQi3Le+t19zOj/Rgz+13EQBdQnrhjClKEoyGZ8izLteunGQ3XiI\npkxLY2AZiyj9jQpzIaZ0CICBQvc3YkGFxk+HhTQLMZgYS3iuzD6rcue8aI8T+MXbTTEULV3Asii4\njvIWKQZW0kXTGAusqL9kHuyYbgwsx3fQAuv8pUqf0VFcm4a/lENK918YurWlSZxoVmTxZfwDHO8l\nUW0ZKGR09yULb4G1JPG7CRKI0G/31H68N6vkKZFTOLwkTmoet+eqnFTSUU1LFRKe1CJRYGOC+oTP\nNToqIYyBjfkQSufHPyN/430XYsP/uNoXv+lC8EBNXZGlfAhdO7mHfHRXZPxlUGR9JBbYHqx9AK9Q\ne58JmCzEAsWJgk3iRJEmDB0JI3w7nbPIUiaKgYXtKCWMN7DLBzsnet6/xz1XXHZ9fIphxDRO/FqG\nuZHP5iV6WtOiW2Al+8eNgbXlSi5Lnyp9dB+0OAU26EIc3QLLx8AGy01Fc8OuNk0U0rprdQ66EIfT\nS5CARb/dU/vx3qySp0RO0WArqgM7l+XUj/tSJRKe1CJRYGOi3W7PKTqzLU8jgigu99JlTgzIgoFo\nllAKd34cm2PFjK/8DSHhD7qi2rQsorjteuRDHqh91jRJlzgiF1zjU1+5rL7UZTQs9jLlcyF2XHrT\nWlCBDLAitcgF+6YFQqCKKq9cs+V82BOiPU5A/HPqIlNhlt0ux2xblDWTddE1rw6syEWYQDIR5qNO\nnJhQG7ZP+eTH1Dl3buqW2zI5C2yEGFh3jICl2nvxEaZair6PfBNrgU1ciBPMBv1yT1VNRyVU8pTI\nKRpU/XrNZTn1475UiYQntYiUxClBEKpSovcbHZUQsfR/X7ccv/naxThjtDe3BcIpOW574JgIP/N0\n5ON058XJatuFDsuHxMLXdc0iLilfikb0mSo0ojE1zgJLQJBNeW7Z3WJ1+fGENVwlcRaOJdF/PU0K\nxI8jKjPjWGCZuQj6+MYT8BBQzESu27yZmDsncnnmkdI9ZbvbixJZDLWmEcel1vZbT4PWcL8F1oho\nge3FysleaglciHlK7NxtLjdxPqO7bu7yLMSRWUvwK4x+u6f2571ZHU+JnMKh2nNkrspJJR3VtFQh\n4UktEgtsTBSLxTlJRyUK+aCSqmsEZ4717nNP5xdwvYyopFBkOzGw3W4pYUa9WstEPh0edxsliZN8\nbLGyzp5jwd4g2YB8tq/OKA88XCuc7ckln/Us5HILrP+Yro0oEzGvKDl8dxRVlzfPgitSCEV7nJBg\n7dswhNU5DYfcgh0oLyOhkNI0zwIrUVZFNFj6KbeMTribOvsyAGBciM1uLsQS5gVwx7DDk0rJFFl2\n3+bTITGwbhbiRINN0B39dk/tx3uzSp4SOYXDywGgRlGYq3JSSUc1LVVIeFKLRIGNCVF851ygoxIq\nXRPo/GT3gKiZ/kzTcSGWxueJg2B9qLUdBTZsKCI9iI5wS6AH3/M+a7n0KUlyBYyNgaX1PFlXa2lS\noh5ciNmsxixsiN2bRTGwoj1O4DfBdostFSGS+hryAqBbMi6KtO7trm4JumTWWI0QmB2FUQ/Rgqky\n6CVxchRX3gLbWxbigJocchTcB77ruXMZnUhjYKn1ONFfE0RBv91T+/HerJKnRE7RYClyIZnLcurH\nfakSCU9qkSiwMdFvX9h+3IStk6HAcu29xu6ePeJYFi86fUh4XmwN8zfWWybymW4WWNYqGM1Cx/MQ\ndWasssc6ZrLXU0VFRJOPlyTgE078/+y9e9wdVX0v/F0zs+/72c8tF0gISUjABAICUe6oCEjQegHl\nqFXboy9afbVqW17aU9qj0h452pfX1tZ6eqinfqq1UmmtFySAgCAgCmgggYRAIAkECMl+LvvZ98vM\n+8fsNbNmzVozs/degf1s5ptPPs+emTW/+a3fWnuv+a3fTcwJf1aWxOljGzoYzyT8fKNbtkdAj6VA\n5cHOccJckyl+IlgC27vfhdh/Hwm6FsErALDlLKqpKi7dJLYq65o/MZfokW5JI/tYVkbH70Is5h0Q\nWdzdz6ZlyS2wQYqsQ5tIY2DNOAY2Rg8YtjV1KNfmIVQURlVO9GdLtPb0g1GVk0o6qmmpQsyTWsQx\nsDGOGI6Ea31YxlhRnCSLzavGcPcfnoejxv1FvYHw2ESAuhBrMAP6dwS6LqXriYGVxN5qATGwbBkd\nkSVbnoRKbIFl+RnPGDhp0p/Mi40b5a2mfB3YIKsqEfARBHEZnfANBndTwX/VX4ZHzI+hESbeN9i6\n7jWuMuNIaBkdK9AN2WeBlez+G1xs8mBZiL3XDy40cOFf34cLTljib8/R0oirTPuzEMcxsDFixFic\nUKW4xogRw4tFocC22200Gg20Wi0n5XMul3POA3YtI8uyUKvVALg1SPnjYrEIAEilUjAMA5VKxTlO\nJBIol8sA7HqhyWQSlUoFlmUhkUgglUqhWq3CNE1YloVGo4FarYZOpwNd15HJZFCv19Fut6FpGrLZ\nrMM3IQS5XA7NZtPZ8cjn8yCEODz10ydCCKrVKlqtFsrlct99qtWqjqypnPrtEx2ndsumRRi599In\ndpxarRaKxSLaba9Vt1atotFIwexaDCuVMsyum3ClUsH8/DzS6bQzTp1OB5N5gvn5eWGfKJ1arebw\nzBuSq80ODGIhaN+q2WwIPwOAaZqo1+vOOAF2KnM6Tu3uAxuNBorFIjdOtYCnAoCF2dlZZLNZmB1G\ncbTsftXrdd8dZnfMy5Uy6vU6LMuCobsW5lKphGrVtlyz48SPBXU7Ls7MMOfsxXthYcFTg5cAaHWf\nW6tVMT8/77h3F2dmPKndS6USZmcJkskkSqUSWq2W049ms4lG3W1br9VQLNojwypCxWIR2WwWnY6g\nlIFloVgsOnNP9L6xsFBGuZxDqyVyY/aiVqs6c8dzvlKG1ZURnaMAsFBeAABUKlXnXIOZM+xcJDDR\nanVgdiyHFgBUymXPM0vzs106TdRqNVRr4lT5ba4/nY7pS6vfaDRQrVYxO++dO63ud77RaMCyLNTr\n3rm558V5PDdbwzOH7Xk9MzODdtoAYKHZanlCDEyzg8pCyeaBV2C7VmM6dtVqVfgb0evv3mKufxdD\njnw+P5J0VEIlT7GcguFu1KpxeBxVOamko5qWKsQ8qcWiUGANw0AqlUIqlfIJmz/mX0r44+npac9x\nOu21xKVSqUjH5XLZ4amf+ylardbAfcpkMiiXy859/fQpk7GVDt0wgLZXTv30MZ/P44WK/cKpacQn\n9yh9YpHP55HP55FMHPacz+WySKVSTvKifC4PTZvtXsthfHzcw2PYuFE62WwW09N2yZ+DzZKnba3V\nQSGbwuFZSMGOQSLhLRmk6xrS6bSnDctTIvGiLYN0yjcO2ewMgqBrGiYnbb4Nw/16J7pZhbMZv+U5\nnbb5y2ZzSKVS0DUNhu4uthPj4874sOOUTHjdghPd501MTLonu2a3sbExT1tCCDTN5imXy2J8fByG\nYQt0cnIKCWacx8cLmJycRLlcduik0rYc0qkUsh1Xhczlspie9v8gUzlqgmzIhJufmsDkXBgbQz6f\nR2reX4aJb2/PnWlfu6mJcSQMW8lKJNyxKXT7lGeSKaRT7jhlsxlMT0/Z9+n7UNfs1M2pZAKArTSO\njY15njk9ZbfXjQQymQz0hN+FGwBy/HwgRPjdSKVSaGheBTadttslk0lYAHJc0rZEkj6TODwVMgkQ\nQpAwEkgkXFkmDAMTExMABC7EDG+2POzn8L8Rvf7uxRhNtFotJWM9bHRUQiVPsZyiQVUIxCjLaRjn\npUrEPKlFHAPbJ4atcPMwFiOWxa32A9o/nwsxk7nWvs5ek9ORIkIMbKtjIRuWhZj53O/CJU70EyxN\nT/IjzvVURpNN5ONkrWVq+Mo8dP0uxN172ZhcabIstx2fxImvK0qfIhw7Iu4nIHY5Fblz+VyIhXGu\n9HEiF+JoMc6G7gbsRo2D5ulrGkHHBGAFx8D66sCKLM8QZSGWz9Ul+SQ2HpV3Skg5SbsgdiGm8jed\n7yY7z7wjoRECXbIaxXVgY/SCYVtTh3FtVslTLKdg0F8tVeV0RlVOKumopqUKqnlSMaeGUU5RsSgs\nsDGOPI5IvOoRoO2LN4yWPycyxAlm/O3SjAKrEb+yFBTvF5p4SpG8+OQ/MtKe7MFdRSRKaRp+LDRO\naQLkcYtsDKwzT7p/7RhYsSIOp00wbzwf/H0eXgJo8G3EZXS4thKCdgwsVf4Ez5BsvnjGkYmBDaoD\nS8/d82QRKUMXljYCeiujY+ga/vMTZ+ET39mGO5847Nuk8SuwYsWTEOIbB424cbs8OnEW4qHFMIb3\nVCoV5PP5gcN7WNf9QcJ7SqXSwH0yDMPxMFAR3lMqlQbqEztOpVJpoD7RcaJeZP32iR0nKqd++0TH\nqVarecJ7eu2TrusOP6ZpOuE9/fSJHtOQjn77RMeJyqifPvFzr9VqOeE9/fSJjhOdS/32iR2nVquF\nmZmZvvtExwmww1/67RPbBxoW1m+f6DhRVOsNNOu1nvvEjhN9fr99Ysfp5Q7viRXYPjFsda+GsZZT\nputSqKL+mds/MS1qzwl7VlQ5hXHMZiHWNQKTy+7qfbmP9Eg/D8JsQsH36IyLLKubUOVARJNaYB0Z\nwnZfDnsmf1qUxCkIVLFxS/x4LXr8c2R1YGXJj6Ly4d8EEZrhPbx47xd7BfCw68BSPoMHUpaMTKN1\nYC2eht+KTAA8eqCERw+UcObaSYjAWt8NjUSycrqZlN2ND7v6kpcHSsqUbFTwNEWu2/b9sQV2WDGM\n4T25XE5JeM+SJUt8PPQT3pPL5Rw6/faJhYrwHpanfvrE4uijj/aFw/TKEzDYuIni+Fg59don2p96\nvT7wXNL1Yvev7oT39NMnelyv15FOp/vuE4tB5xIF5SmsfdhvBD+Xeu0T+8xEIjHw940eT3VDcvrp\nE9sHTdN8PA0SCkP0BCYnB+vj0qVLfd/ffn/LX+7wntiFuE+02/7MqqNARyU6HTeJ06Cg/YuiCwe9\n5obJKVKZFABZpg6sOKMs4y7Z44t3r6WB5IRY11qXOg9DdxVP193JdTmV8iNxIWYVDakLMSGMaynH\nmcW7Qtt/vWNHlW3itRZ7XIgFFlgRL3z/hPqrfAMgah1YQ3fL6LDPEM45yZFO0LXAItQCy8oligVW\n1/yWURFEU0nsQkwtp+JxYE9rhEgtsG3HhTictxgxhm1NHca1WSVPsZyiQdX+2yjLaRjnpUqo5qkl\nCQ3qBcMop6iIFdg+MWw+/8r82BW+JNKMrVFf8INA+9cLLdH7cJicoho900n3q6OH8OSrgxmxD30Y\nYL2KH3OeWrdE8nPjJbv3k2gxsD4XYoEFVjadCFwFJywGlvaEHTs3s6Pc3Vb0bKELcbj+2lsMbKAL\nsfge330SBVfXNLRNC5ZleeYdT42AeO6TKbBe2lEtsPZfNgbWPva242NgHSs28Y+DromTZwFMHcXY\nAhsjAoZtTR3GGLNhjDUcVTm5niiDKxvA6MpJJR3VtFRBNU8qFNhhlFNUxApsjCMOFS7EDq0QFc5+\nOe7/RTcogQ8LNomTqH9eV1aFSZxCREkkig+vJLJwLV+sVZOhI3uW5NmWxwIr55NVQnl6psACy8LR\niQjh+sm0EVr+/Od8CmyARTTq/BAhoWvO/A3biJEp5brmlibSAiywfBxzqyNTYHkX4mC+WH6cWWO5\n84YFPe+LgZXwEbYRFFtgY8SIsdjgejW9omzEGEHI1vVXC+IY2D6hqobgsNFR5b0KAOm07QevQn+l\n/ZPSipDUh6UTBllCHQo2BtZWFrwv2N6Mq3J88V0nYlXB+zUUeJlGhiwjr5vEyU/VY4HtnsswMQsy\nmfuzENvHrLVPpryzFlievGVZwhhYduy8yqlYaxc+WpjEiXfYFW0cyEcjqgVWZyyw7DNc92RWIRUr\npxoh6HTHyZtoi++DV0numOKdWraNoRO0IyyIbgysfezIWWKBFSfc8j5HI3ILrEvv1b1Yx4iGYVtT\nh7HesEqeYjkFw/19VPNyNapyUklHNS1VUM2TCgvsMMopKmIFtk+ocmcbNjoqXYgtiYJyJGmFWXvD\n5BRVeUlzZXQ04nW/9LiyBjzy3aet8GSB8z43Gn8yeCx3Abe5SZzcWEbCTARZwiH+tBsDG4E3Rl5u\nXKjLh3czwP4rGju6ecDzYPPhtu+YdtZeEWtR3NJdC2ywtT0IuubGwIa9y3j75N2IMLtJnIJiYG3L\ntHuSr60qop3UNTR6iIeh9F1XcO91PvkSm6zLPuWdY0aIIG0X98jsxXiVYtjW1GF0fVfJUyynqLRU\n0RldOQ3jvFQJ1TypsMAOo5yiInYh7hM0bfSo0VGJphO3OrgKS/snVVAjKnthcorKajah+7LDyuiE\nWY54ngaRlufHiCF00ooCAOA1R/mzNbIWWHpbq9UKfRYvXzcrbbgLsed5nMWZV27oc1g5sUY/r7Xc\nPWB1NrpTKfyxjuBCLGkKQGSBDbLW+u8RWdxln20LrN2H4BhYr0IpU2DZ+1KGFtECS3mx/7pZhr1c\nmD0kX+JdnmVYvEttjJcLw7amDuParJKnWE7BoGErpqIYiFGVk0o6qmmpgmqeVFhgh1FOURFbyVr4\nIAAAIABJREFUYGMccahQYCmiuBCrfskVPZN1IQZEVrgQV9ZoT5bycuox4/jQWavwRzftkN7Bfn7b\npuU4ddU4ji74U+nT0jtW9x/g7Y9MIfNbYKlFzj0nTeJEXFdjfxInS2iBZeEqv8TrjkvYNi6RVsdC\nOhEtC7Gwt14jMdeXCPdzbUPrwEp82F0LrOXdNBFosOz3TqaYss9JJfSeFkTCbVjwsnFdiP3eEzw3\nGiG+mrQixApsjBgxFhXo72D86xVDMZoKFNjFjNgC2yf4OkeLnY46FdNFitYSVUCc9i/chVj8macT\njuAnZRLer05QHCS/cPF88TxFcTNdXkhh1aS/L8TjVup+1jSC45bkhDSp6yZb1ibN1hqT8ODPQowu\nnf5iYFkLrMiQLBo73gLrSeLEtAtSzHx6k9CaL73UU2ZsJwbWE78aDFbB1gjQoWV0QmNgWRfi8BjY\ntKHBtGxLQbAV2quE03nDfwccywOfxElAWyMkmgU2fgeMEYJhWVNV01EJlTzFcgqGOLCof4yqnFTS\nUU1LFVTz1GwPviAOo5yiIlZgYxwxOMlpFNKUuWuyLqWDvOQKM/8K2mV8MbDye/r1HBI9V2ZhFYHl\niSo7onscyxeTxclrgZXxJxkL1gIr6btGCKhO6VolXXqmxBXaxwPhL7M03LOuC7GYhpeCyPJNPH/F\nTxTTE9ERWmAlNNjPtgXW7kdwFmKvYEQLHe+2mzLs5aBtWoHfIfcW+t0TN3bLR/h59G1SEDvDchhi\n/TVGjBiLCU4ZsFeWjRgjCBUuxIsZsQLbJ4bN538Y/djr9ToAtTGwPZlgg+j0AJHSkmDetgngc39k\n+8zHXfIKkoynIHdVQiCUhWWK93upsiPqiyeJU5c/WsOXpxPEHxVBJ8IOAiH+5D98UiD3+fZ5kZwI\nvH2SldFpdl1oI7kQhyiXvms9uBCLLLBCmpLPNAbWb4H138/KotHuCJ/BspHqbso028GLIr3Fb4H1\ntqPj6J//YJzV6b2xBTaGGgzbmjqMa/MwxhqOupziGNiXj45qWqoQx8CqRazAxvDgSMRp9OJiGQae\nlOoMamFWTwqfxTXIhbhHFqOIi4D4FC/+ZspTWGyhL4kTZ5nrPQY2ggILNgsxvR/d+yPUgWWYlVkr\nWTacH3pJJuNQfon3LwuffAOTOPktsHwWZs85eMdC14gbO8z8eouzI7vnGm3TsbCy93gU2O71sLga\nnl03BtbLAyXjJnkK4jV8ngKxFSNGjBiLC/SdKo6BjaEacR3YRYB2u41Go4FWq4VGN7NtLpdzzgN2\nLSPLspzdBOrXzR8Xi0UAQCqVgmEYqFQqznEikUC5XAYAJJNJJJNJVCoVWJaFRCKBVCqFarUK0zSd\nZ9dqNXQ6Hei6jkwmg3q9jna7DU3TkM1mHb4JIcjlcmg2m2g2betWPp+HaZoOT/30iRCCarWKRqOB\ncrncd58ozXbXUlMsFvvuEx0nes6yLKePvfSJHadGo4FiseixDALo9j0JsxvjVymXYZp2HyqVCubn\n55FOp51xorzJ+kTvrdWqKBbtz62W113Yfm7Faxnjrje61mcAaHIZfTudDur1ujNOpmk648e2r9fr\nKBaLnnGicrHMDsrlBR9flmlhdnYW2WwW7bZNRyNwxqNaazhtbUsYUK/bNCvVCur1Bjod06P8zM3N\noZrzWkEzmYwvU7Fptrvt5318LSwsIJlMspyi1Z1r1e44dTr2/TMzM2g2Xdql+XnMZuzvWKlUQqvV\nQq1u96PVbKDO9KlaqaLYsOXIKsGHi7M4OqcJ66Fa3e8gnXuWoM1CqYRyOYVW05+d2TK91s1qpeLM\ndxZzc3PodMvUtBnZLSyUANhzl6Jed3dF7bnYnfdmBx3ThGUCrWbTQ6NYdMdsdnYGsNx+tDoWxlIa\nGmyVHMtCs87MB9PmaaFaB4tGo+H87hmG4XzX6rV697rNR7Va8dxH5weVeXFmBilDg2WaaLXanvnT\nbrcxPzuLMFiW/Z0X/Ub0+ru3mOvfDQvitfnIr830e5fu1uZWsTaza2A/fWLHia7N/fYp6toc1id2\nnKic+u2TbG3utU+6rjvvVJYFZ23up0/0mPLbb5/oOFEZ9dMnfu6xa3M/faLjROdSv31ix0nXdczM\nzPTdJzpOgP1O0m+f+D7Q35R++kTHiaJab2B2drbnPrHjxP7O9dMndpxe7rV5USiwhmEglUohlUoh\nn/eWAeGP+Y7zx9PT055juihQpJjkNUHHtVrN4amf+1n++SDqXvuUyWRQq9UcOv30KZOZAQAYhg50\nvHLqp4/5fB4zTVut0zTNJ/cofWIxOTmJTCaDdKrkuy+VSoEQ+1ljY3mQrmkql8thfHzcw2PYuOm6\n7tCdnp4AAFRn/HVaC2NjnmPeepTOuGOgG96vmWHoSKfTzjjxPCWTL9k8ZDK+cchm5x0+eR4AQNM1\nTE5O2nQSSYc3Sj+Tzbltu9a8Qne+ZTJZJFNJ6LqGTNqVz+TkhDM+7DilPAopkOwuimOFgo+vMY5X\nTSNAd8zy+TzGx8eRTNg/auMTk9CNg07biYlxTE4WPHM8lToEwE42lTXd7YN8PoepnM0X67GVHSt0\nFwy/04mu6x4564JgzPHxceTzeaQa/rlgcOOby+V8893uxwQSCfeHm6IwVnDk4PDLzH97LtrySyZm\n7X4RIMvMsUKh4Hnm9NRUdy67Gms6qWOh4SrbhBBkWBq5DIA5EN3bH/77Qr8juazNo07HPZfz3Kd1\n21ndrZ4l09NIGho0TYNhGDAMV8FOJRNYusQvMx4m3DnI/0b0+rsXY3DEa/ORX5t5qFiba7Waw0s/\nfWJB1+ZBeAIGGze+D4BXTr32SbY299onANB0e60CgbM299MnekznU799YjHoXKJg53hQ+7DfCHtN\n8q59LHr5zY/KU5Tjqakp6fVefvf4/gEDrmOa4cypSO0Fx/zv3CC/5S/32hy7EPcJusMwKnQUhKn6\nQHdlVLgQ0/6FhsBKSqrwdOT3i06KXR7dy8RfB5ahtGws+Msp40nozixxl6WwBK63MndgyrLOxMDS\nNs2m11Irgj8LMXUhltzAtXVdYYnnr2l5na2oLFk5sbx6MvpKmHWSOAmuRUni5F4LPxf0XXLrwIbx\nIRkzzS4/ZFkhMbCE+J6RMnSuDZ/EqbcYWF/SLq7jfBkdcM1YC3nkMjqvbo+pGBEwLGuqajoqoZKn\nWE7RIEkE3zNGWU7DOC9VQjVPKmJgh1FOURErsDGOOFQqx2HJb44EfbEi6VVzgsIgL9qwFP/4odMw\nnfNaLMOZkZ+yk8xGSwTEKgae5EBdJhNMDCxVENj+SJPrSOJ+o8QlE7B1YL3PNAUZaoPoeMdB3Dgo\nViSoBBJ/TnTNn4E6SgwsuxMRTJO9rBNiywfcuIbEwALwxcDa97mf093rjTAF1jde/jqvgDsPRBsa\n/BzRSLSNrlh/jREjxmKCm4U4/vWKMTi89e3jLMQx+oAqd7Rho6MS1MVURRZi2r8wUmHXo8rJq+iF\nt/cpQdzR+eunHYWDJ8fz5CipwblvA7MU25/tv7rgnM1z96+jwFrdLMRe92Cp/sodUxl0IphgSTeb\nLkvHtehZQiWYlZObxImzSkue55bRGewlQkSft74H3u8OroC2eJw8Y6a5MpYpufQeXqlNC5I4icro\nhCZxouWxmA0HQJSFmP71JusisBVRb6KuaBZYRYk8Y4wwhm1NHcq1WSFPsZzCoPZHa3TlNJzzUiVU\n8MS+woR5S0XBMMopKmIFtk/wcW+jQkcl9G4snQqrKe1fGCUCBK4X/chJpkjSbtnKhLeNJlAaZWLo\nhSdPGZ1QXrvWPkm2WvrJ8LkQAwmGJ5nMeR74sioinLA879xLywrwtVHtLMR+nkVy4rMxy+ZaK6iM\njs96HmCFF14Lt+Dy18I2dTx9Ys6zmxFeCyx/v1+hTIZYYOn1UBdiZz67Gw70mH2mW0ZHTIAdY73r\nCh72UxHrrzHCMGxr6jCuzSp5iuUUDMcCq+jHa1TlpJKOalqqoGQ+MZ9VZCEeRjlFRazA9gk2E9go\n0VGJSsS41Ui0uv2TKSjUPcdrufK3DZNTkPsoD6N7vtUxA12IKWQGJp6nMCUVgK/+KYXFZJ51Ylwl\nhKg1Txe4EDcaTCZa2f0SpT3Iyvmt/7oZN33sDGjErRfLK3X+GFgbrJy8NURDWWUssOH9EMEZE8E1\nvwuxHMIyOs4z2Of5nw14lVbPJomAX/5cOsHFwHI06PVQF2LuL2MM99DzWWAZGpbFx8Daf2Vzlb0v\nRowgDNuaOpRrs0KeYjlFgyrvkVGW0zDOS5VQwZOp2IV4GOUUFYtX9Y4x9BAplYMigqqhnL6MIjVo\ntTpWoBspvaJFUEx74SXUGk0VQwlvKUNDpdHhkjhZvrhSqQWWO45igZ3IJjCRTdh1YE16n1c5tCx4\nNBWhvJiatayCl5D0NeiH3qf8BbQRb0xEt8BS9kLHTkKP7V5QDKxog8NfB9ZLm7oYh+7qCjYcKA8s\nPVkMLEF3+ARWdk0jgRMo1l9jxIixmGA5f+NfrxiDg93ErTQ78oavAsQW2D4xbD7/quiotHAkEupj\nYAdN9BI5BjaCVc/wKBa8EiNwNZUQkvEUlkwoNAa2q2nIrFrpbtZZx4WYUUTSqQgxsNx5XqEJAmEs\nsI5Sx1hwPS7E3b8iOfGsyeIom9SFWMCb34VYzK/9PNG4Ch8phGtd9yufHjICCy0gt8CKePJnIfb/\n3HtiYBODxcDymwl8FmLes0BsgQ18dPwKGCMUw7amDmOM2TDGGo6qnJw1R9GP16jKSSUd1bRUQel8\nAjBX9del7xXDKKeoiC2wfYIWgh4VOmEZbfuBGwM7OC2nf2GxgyHPCpOTWMkUE2XLhfIv3iILmkz5\nlvEUXM5FfFWUxMmQaAU05lHkQszyJI8BFivtUTZBCCFODCyVlicLsYAuy5P3uvtZpsDSZwljYEOO\n2bNRLLBB9tW+YmCZtux9uie2OZwvnwWW45SW0Ymehdi78cFnEjYlFlgAuGPXISGvYQmxYhfiGGEY\nljVVNR2VUMlTLKdgWNzfQTGqclJJRzUtVVDBE7uezlabA9MbRjlFRWyB7RPlcnkk6ahEmcatqqDV\n7Z+MFhuHF4WODGKlUNyWtcD6lbkg2t6LvYwd68oqjIFlft3oVUOiFKQTnALLODk1am5tMKkFljvm\ny6oEgcBvgWUtuCIaIjkRwm8WiJkNyowsU8T551C+eUSJf3bb+hVhdkxFNFhy3thZ2YyCL6ESIIiB\nJd4aulTBbUWMgaVwLLDwZjWmQ8jHwAZ9x2Rz1aEZeDVGjOFbU4dybVbIUyynaFAVAzvKchrGeakS\nKnhi341mFVhgh1FOURErsDGOGNystuqsu2EuxLIX/0Ego+OxwHKMeZQqx3oXjSMrgjYehZKTvVem\nwBq6xxXZeSynHMueJXMh7kRQYDXCZiF2z1E+wurAOm6pnNIkgzQjroS+r01AW1H8qQx8zVvxU8QW\nfN+zAjZQROfELsTM9US0OrD8vbJYd17mURT7sLGMy+h4MTs7iw984ANYsWIFNm3ahO9973vCdnNz\nc/j4xz+O9evXY/369bjuuus81x999FFceumlOPbYY3HiiSfiy1/+8svBfowYI4/YaySGSrDzaUaB\nAruYEbsQ94kkUydzlOio/K01DNs1oYcymVLQ/oUpgQQkcMGIKidZTU4WXgssd7/gJjfWMxpPYh0n\nmC+RFc/QxftUSUOzy5eAWmDdH8dUknEhlvTfl4W4+5ioLsQ0V5BrlXQtsGycB30KKydv3GX482hY\nZxQXYjG/8ta9zG9RDGzw8/jNkPDPMr7CYmDTkcvoeJVNdiy8LsT0r1fqQd+NsFqw8bugF1dddRWS\nySR2796N7du3473vfS82bdqEjRs3etr96Z/+KWq1Gh599FEcOnQI73znO7Fq1Sp88IMfBAB89KMf\nxW/91m/hxz/+Mfbv348tW7Zg06ZNeOtb3/pKdGsgDNuaqoqOSqjkKZZTdFiWNfCG/ijLaRjnpUqo\n4IldA1W4EA+jnKIitsD2iWH7wg7jJDS6vvUqLLCOAsudH8/4/feXjtltCxn//kyYnHph1SDuTwmf\nKEmkSMqsSzxPbD1WH3/MB7Erpt+KJ1MKjplMY9lYymOBtbpZiFNJNomT+H7+bM9JnKgF1rkf3fvF\nMbA9KfocOiYto+PnLUoWYT5xUa/3u20pPX97r9LKblTIrK7BzwyNgeWUf+piHJ7EidK3/3rrwLoE\n3SzE3iROQpoRLbCxNcNFpVLBD3/4Q1xzzTXI5/M4++yzsWXLFtx4442+tlu3bsVnPvMZZLNZrF69\nGh/60IfwL//yL871/fv344orroCu61i7di3OOuss7Nq16+XsjjIM25o6jGvzMCoKoyonds1R8fs1\nqnJSSUc1LVVQwRNdT7NJHXPVFpNL5JXj6ZVCbIHtE5VKRUn2rmGjoxKq68CmUimH2JrpLP7ufafg\n6PE0AK/S9+kL1mH90hwufM1SOR0JhEqhpAesPuBTYgTtg+rAijPsBrzwgwgVAo/lMsSF+CPnrMY1\nl74GD+6dte+Fq2jU6zXmWVImPIhSRoe9tcMpNmxSIFGGWlZOnpIE3fuCrHeBlWF463lAU9Ej/HVg\ng8fNvqcHC6xMsQ2xwfLzQ1QHlm2SimiB5f2p3RhYb786jgLrvb0tmCCuBTb40bH+6uKpp56CYRhY\nv369c+7kk0/GvffeK2zvfZG28PjjjzvHn/jEJ/Dd734X11xzDfbu3YsHH3wQn/nMZ0J5KJVKuPvu\nuwfohYutW7cqoTPqiOUUDcMip337NVBb0S233hqaaf3lxLDIaNgxTHKqtADAQIa0UbUIvn/zrcgN\nSR4mVXJ629veFqldrMD2CZElZ1HTOQI/qnRnSIULsZvp1FXKjl+WF7ZNGhredeqKQDpSBCTwoaD9\n8Siw3Iu30NpE3Ud75UnAC5+8KKitTIHNJHTkU4ardDCxpyILIQ9Z6aAo/dEIcayivGu1ycfAdv/K\nSuAEx5V2adIsxKIYWIj7wT9H1FbUPpIFVmBUlclc5s4eZoH1uar7LLBeiym93qsF1rSY7znzTL6M\nDoUooVbUGNjYAuuiUqlgbGzMc65QKAiTclx00UX4yle+gq9//es4dOgQvv3tb6NWczepLrnkEnz8\n4x/H3/7t36LT6eDqq6/G6aefHspDoVDAli1bBu7L1q1bldABgGKxiOnp6ZGjA6iTk0qeYjkF41c3\n7wJefA4A8Ja3vAWJsF26l4EnYLS/cyppDZucZipN4KF7sGrpBIrPzeP0s8/H2iW5V5QnQK2comJR\nKLDtdhuNRgOtVguNRgMAkMvlnPMAkM1mYVmWsyhnMhkA8B0Xi0UAdu0jwzBQ6WbKTaVSSCQSzuKf\nTCaRTCZRqVRgWRYSiQRSqRSq1SpM00Sj0UCj0UCtVkOn04Gu68hkMqjX62i329A0Ddls1uGbEIJc\nLodms4lm0/Zbz+fzaLVaDk/99IkQgmq1imq1OlCfal1raafdduQ0SJ8ajQZq9ToAwDRNp4+99Ikd\nJ3rc7Mqm3e6gWCw6fbK6ytDCwgJyRt4ZJ8MwkE6nnXGq1+toNBrSPtH+12pVFIv255bmtY5qhKBc\nLnt2Ui3upZy1YNbrNdS0DqyOXXSa8kHHicqLjlOz2XJkUiwWPeNE7zFNEwsLJfAwTROzs7PIZrNo\nt1pd3jpoNBqecQKAdqOGYrHq0KlUq2g0mjA7HcBylZjZ2VlktYJvnFpNb/xFp20/b7604ONrYWHB\nM/dM03QUmYWFBczPJx3Zz83PodX9DNgJaPKkAcuyUCqVbHnVG13Z1lGt28+l40K/P57nVyqo1Wow\nTb9yZnbaKBaLztwzO/7i4KX5eZQndDSbfg2K9puiXC6jWNR97ebm5tDu9ovlsbSw4NxHwSoX1WoF\nxY497m3mWfQ7CwALpXkUiy7fxWIRJiNDAOg0ap5jWBbqzHNqZXse1Bre/jQaDc/3icqQfidbrXaX\n/woIo2F2uoow/WrQ34BW2y/fVqtpX7fEyrNObCu61X2u6Dei19+9bDYrfNZiQS6Xw8KC97tWKpWQ\nz/s39r70pS/h6quvxubNmzE1NYX3vOc9uOmmmwDY3+/3vOc9+PKXv4wrrrgCBw8exO/+7u9i2bJl\nuPLKK1+WvqjEsJX0GMYyFcNYrmRU5cRuuqnYgBtVOamko5qWKqicT1Nds+tMtYW1rzBPrxQWhQJr\nGAZSqRRSqZRvceaP+ZcS/pjfaUin055j3pVTdtxoNBye+rmfYnJy0neu1z5lMhnk83mHTj99ymRt\nN1LdMICmV0799DGfz2NywQKwD4au++QepU8sli1bhlQqhXS61uXTS5NoGoAOxsbGkEol+x43wzAc\nfqanxwH4A+UJsceITeKUMLwKS5bhP5PJIJNJIpGwaeu6jnQ67YwTz1My8RIAIJfN+MYhn7NfWHVN\nw3ihAB6GYWByctKm041tSHfl4Zt742MYzyRQmLF/EdOZDFKpJAyjhULBtexMT00hm006cnH5qXro\n0bjZbM7/Ak0tRa6cdZhNW1kZHy9gfHwcqcO2IpQfG4euH3T5nJzE5GTGkRMAJFMvOrKFnuzKhCCf\nzwtf4NPpjK2gCsy0iYThkbNh+JXP8Ylx5PN5NCv+pAkpLoZkLJ8X7mhOTEwgdbDV5ccdCzqOY2Mu\n3zlGzvlcDtNdV/lkwlU42bEYHx/H9PSEczw9PY1k0rswTU14rXWaRjzPOWqJzXPb4mJnublj6C/Y\n/ObsXV9d1x3+dUFxWtOy46qpTETu3OlUCtPT00gYBgC/jKfySayeyiKhHXb6zf9G9Pq7t9ixfv16\ntNtt7NmzB+vWrQMA7Nixw5fACbC/QzfccINzfO2112Lz5s0AgL1790LTNLz//e8HAKxcuRKXX345\nbr/99kWpwKoa52GjoxIqeYrlFAzVTiOjKieVdFTTUgUVPFGPp6mc/d4xN2Am4mGUU1TESZz6RLVa\nDW+0COmoRK1mW2BVJHGi/dN6cFMNoiNDUAIftw2NuXTP+eMg/fe77r/exjxPQeWH2Cy2ouushZFe\nlbkQ05hH1/XXlWujaz0Pgs+1uvucoJqrLG+++qCeGFj/c0Rjx3qtBrkQt3twIRbz6x1DzzX+nKDN\nqceMd3mkbuSCsY1QRod1sfUm7Ap3fU8ZfAws8cbAJiK6EHM+z3SsNOLlwk3i5L0/OAZWPBZnrJ7E\nv3zkdViWEV5+VSKXy+Htb387vvjFL6JSqeCBBx7ALbfcgve+972+ts888wxmZmbQ6XRw++2345vf\n/CauuuoqAMC6detgWRa+973vwTRNHDx4EN///vdx0kknvdxdUoJhW1OHcW1WyVMsp2Cw7ypREhyG\nYVTlpJKOalqqoIInunxOdBOYluqDKbDDKKeoiBXYPiFyRRwFOirBxzgOAr5/vmUg4roQJicRq9IY\nWOa878VbWCpELIh+xo5PwCNsExIDm+xq4E6Mafc/ATyunLLn8KfpY6IosBpx27nxj/Y1u4wO+5yu\nJY+Rk+c9IET5oTQB7zSRlTUKmgMiRdGfwMt7/M//9XR843dO8xAPHzuxoipv7z8XloWYb+OW0bGl\n9I6TpvHdK1/nfxZ3r5tl2MsrW0aHZaUtMMHSzQ/ZGKqsJT1KuP7661Gr1XD88cfjyiuvxPXXX4+N\nGzfi/vvvx8qVK51227ZtwznnnINjjjkGX/jCF3DDDTc4ltpCoYBvfetb+Pu//3usWbMG559/PjZu\n3OgouIsNw7amDuParJKnWE7RocKFeJTlNIzzUiXU8GRPoomsrcDO19pBjUMxjHKKikXhQjyMoK6m\no0ZHJahroaEg7R7tX1SlLYxOGIjkM8AmkmKfS7g2fp5krMl4EluD3Q9Cy6HAWidTCqjS4ORwYlI5\nJxMuTzILpb/PPVhgCWEUWO/9puXdtXYUcYGc7CRO4QmAnDqwDGsaIT7lyvNA9pT8UugGzdolOeRT\nhofHKBsl/LP5NqJEUEF8+RRY4m1j6Bo0ArS6wjpzzThOWzUBHm7WaPvYciywfB1Y1+rNng9K4iT7\nqVCxCTaKmJycxHe+8x3f+XPOOQcHDhxwji+77DJcdtllUjpvfOMbcddddx0RHl9uDNuaOoxrs0qe\nYjkFw5J87hejKieVdFTTUgUVPNHlczydACFAqTaYBXYY5RQVi5fzVxh8vNWo0FGZ5fP0NdP4yDmr\n8aEzVw1Mi/ZvUEtMmJyC3HZ5eCywPiue3FLHX+F5iuIeLbPAasRvZUuEbCC4ip9r+cwwPMmzEHM8\nUQts1DqwXBkdV5G2IDCweuTklPxhrgcpsK4F1q8Y+1zEJfzKrxFhWxE91+obPCbybMOMZVb2EAlf\n6QSXhVjQxtA1p4wOH9vro08t4+7Oh2cMZPsYLcGOr7OJIdtsiS2wMSJi2NZUVXRUQiVPsZxC4Eni\nNPgL1sjKSSEd1bRUQQVPTtZ/DRhLGZgfUIEdRjlFRexC3CfYLKGjREclGvU6/viS47FiYvAvCO0f\nb/Xpl44MQgWFOxbVrPSXlPHfL3sHl/EkbO6xsPovWwLX3yDXWu+9rgsxGwMru1tmmY4WA0uc0jZ8\nbLAFb6wQvc7KyXkEceM4+VJGLJy4S4Y1nbNA88/j+WV5ZBGlBjDfVmRVlVn95bGxxNfmjce7yaN4\nvvgyOuyzKQyNoNFVYFst8cLojpf91ym9RLz0PC9rzAWhC7FjgZUpsMLTMWL4MGxr6jCuzSp5iuUU\nDI8FVoGBYFTlpJKOalqqoGQ+MTknCpkE5uuDuRAPo5yiIrbA9omOoNTGKNBRCZU8UVqy91gronNO\nZJ5k2gTE7o5R4ihlViSep6AkTrDYa/7rovqpRpBmB5d3NpbRYqxkMr4HcyF2lVDXgkr54Bf6Ll3B\n2NlSCFZ+AKYOrIDfoARcLL+ya35LdMBmhrObIWXVRyOK2zA9/3fvey0OHDwk5CvNJ3FOJFy4AAAg\nAElEQVQiAiVX19wkTpKSNvyGjJvEycu3dxow5XUE84PfbMkkNNRazPNjBTZGRAzbmvpqWZuHhY5K\nqOZJhYPbKMtpGOelSqjgiW4MawQYzxgDuxAPo5yiIrbA9gka3zkqdI7E+6GqvnlohblehvQklCeh\n9c2LKO6MIrdP3nIVxpPoKRZzTWgp9Fho7QNZEif+OX9z59O4Y5et/CQSur9BwLPs59l/RVlmeWiE\ncYXhYljtJE5+CywrJ5FxL8jSLHJrdtv3MPuFMo9+v+iJxPdBbnEUKa3s+aShYTKXErLKW2AJiO85\nhk4cF2JdsvFBuPGiY8XT81jRGW7EWYi9mx+5lHdvNWwTJkYMimFZU1XTUYkjsjYPCR2VUMETu5ap\ncCEeVTmppKOaliqo4MlkjBjj6cTASZyGUU5REb8V9Am+BuGo0FEJlTxRWq4LsXchiLou9MOTT0GJ\npMSIXE1740logGUzvgru0ZgXfSf5UUgMLOX94f1z9jG8dWxld/Pns0n7h9CM6ELc8bkQ23+pKzP/\nHJGcWLfVIEXSFJTRkWYhDqATyQLru4cwbelmhp9SlDI6sg0c9jSVky++VTAB+TMJnTgWWFl9OL8F\nVjwne3lXo6zVu8pznlNgYxfiGFExbGvqq2VtHhY6KqGCJ9VJnEZVTirpqKalCip4YtfbQsbA/IBl\ndIZRTlERK7B9oh6hTuZipKMSKnmitOhLfr8LQRhP4vqcwcdCOgLrmGOJ7ZEnIX2ILcGW6Vf9wmJg\nff0jBM1Gw3MsvK97fjKbwF+9+yQcvywPIJoF1uNCLLDAiurAeuXEWmi7/QzoZscCGq2Op8apLHux\niAwJUDx94xDAh2gOCF2OmXOe2q+Sx7DzlsqJH3Y+mZet/PNKrubEwLbbwQsjccZLTo99VhRa9Zbt\nzpRLeneFw7wIYsSgGLY19dWyNg8LHZVQwRO7kaeiDuyoykklHdW0VEHJfOr+1QjBeCaB0oAW2GGU\nU1TECmyfaLcHmzTDSidqLGkUqOKJpSV7EY7qxRmZJ3H+GQBixZE/I3rflrke8zw5SXEC2CJM8iLv\ndUH5mYgxsCxMJi5CJlrax3zKwDtOOdpXFzTqM90yOnDutwTup6ycXBm5qpssgy1gu6ae/sWfYYFJ\neOAkcfIxJ+BXfinUOijqa5j7t1RRlRyw56mc+PnGb2SINkEMn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6rva0igaltHGws4rlXF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\n",
            "text/plain": [
              "<Figure size 1152x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r468/468 [==============================] - 3s 7ms/step - loss: 0.0799 - acc: 0.9766 - val_loss: 0.0844 - val_acc: 0.9770\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "9jFVovcUUVs1"
      },
      "source": [
        "### Visualize predictions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "w12OId8Mz7dF",
        "outputId": "4842abbc-b491-46f4-db39-354611936a2e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 585
        }
      },
      "source": [
        "# recognize digits from local fonts\n",
        "probabilities = model.predict(font_digits, steps=1)\n",
        "predicted_labels = np.argmax(probabilities, axis=1)\n",
        "display_digits(font_digits, predicted_labels, font_labels, \"predictions from local fonts (bad predictions in red)\", N)\n",
        "\n",
        "# recognize validation digits\n",
        "probabilities = model.predict(validation_digits, steps=1)\n",
        "predicted_labels = np.argmax(probabilities, axis=1)\n",
        "display_top_unrecognized(validation_digits, predicted_labels, validation_labels, N, 7)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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3/V18CxDWu2qL21TeJZhvCdH1xcPDgwDQoEGDakwzdOhQGjp0KAEgDw+PBr0q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\nBoPBYDRCWKDOYDAYDAaDwWA0Qv4//roIheJmKtoAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Tp9P06dPJ0tKSvvvuu1qnWVhYSC1atCCO44Rt5cqVFB0dXfsM/4OYPHkycRxH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\n/wc5osRNkOQffAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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/ae2TlpYmeNtjYmL0Om6nE+ojR47EiRMn4OTkJJysWq3usGeIp6CgQGh8Dh06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\nrkJggg==\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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b1uDRo0c0c+ZM2rZtG+3bt4+GDx9u1vFGjRpFGo2GRo4cSUREXl5e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\nNggX6hwOh8PhcDgcThvk/wFb1ewk9dTwDAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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GEI8eParnebaxsZGsPd+7d6/WEBSFQkHdu3cXzXDV1fD19dUbLj579qyeoc57JcWIweTD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\nQmCC\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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fH9HR0Sbbfvr0KcLDw0UPeWxsLPLy8lBZWYm6ujrExcWB4zi0adMG+fn5yM/P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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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hsz4+PnTr1i2t6/Do0SON4FVD5pOoVCp69uyZpPMO0tLSqH///sI9IjIyUrR9379/nw4f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\naIT8P7WnwB5a+qeoAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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V1pKent6gnvF5kslktGjRItG04uPjydvbW6UBVfeBt/7n9evXt1jr1q1blJCQQG+99VaD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\n1ufNAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "SVY1pBg5ydH-"
      },
      "source": [
        "## License"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "hleIN5-pcr0N"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "author: Martin Gorner<br>\n",
        "twitter: @martin_gorner\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "Copyright 2019 Google LLC\n",
        "\n",
        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
        "you may not use this file except in compliance with the License.\n",
        "You may obtain a copy of the License at\n",
        "\n",
        "    http://www.apache.org/licenses/LICENSE-2.0\n",
        "\n",
        "Unless required by applicable law or agreed to in writing, software\n",
        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
        "See the License for the specific language governing permissions and\n",
        "limitations under the License.\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "This is not an official Google product but sample code provided for an educational purpose\n"
      ]
    }
  ]
}